Slow quires and facets

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Slow quires and facets

Rudenko, Artur
Hello everyone,
I'm am currently investigating a performance issue in our environment:
20M large PARENT documents and 800M nested small CHILD documents.
The system inserts about 400K PARENT documents and 16M CHILD documents per day. (Currently we stopped the calls insertion to investigate the performance issue)
This is a solr cloud 8.3 environment with 7 servers (64 VCPU 128 GB RAM each, 24GB allocated to Solr) with single collection (32 shards and replication factor 2).

We experience generally slow queries (about 4-7 seconds) and facet times. The below query runs in about 14-16 seconds (we have to use limit:-1 due to a business case - cardinality is 1K values).

fq=channel:345133
&fq=content_type:PARENT
&fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total of int 562 values)
&q=*:*
&json.facet={
                "Chart_01_Bins":{
                                                type:terms,
                                                field:groupIds,
                                                mincount:1,
                                                limit:-1,
                                                numBuckets:true,
                                                missing:false,
                                                refine:true,
                                                facet:{
                                                                min_score_avg:"avg(min_score)",
                                                                max_score_avg:"avg(max_score)",
                                                                avg_score_avg:"avg(avg_score)"
                                                }
                },
                "Chart_01_FIELD_NOT_EXISTS":{
                                type:query,
                                q:"-groupIds:[* TO *]",
                                facet:{
                                                min_score_avg:"avg(min_score)",
                                                max_score_avg:"avg(max_score)",
                                                avg_score_avg:"avg(avg_score)"
                                }
                }
}
&rows=0

Also, when the facet is simplified, it takes about 4-6 seconds

fq=channel:345133
&fq=content_type:PARENT
&fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total of int 562 values)
&q=*:*
&json.facet={
                "Chart_01_Bins":{
                                type:terms,
                                field:groupIds,
                                mincount:1,
                                limit:-1,
                                numBuckets:true,
                                missing:false,
                                refine:true
                }
}
&rows=0

Schema relevant fields:

<fieldType name="pfloat" class="solr.FloatPointField" docValues="true"/>
<fieldType name="pint" class="solr.IntPointField" docValues="true"/>

<!-- Currently only 1 value, in the future we expect to have about 25 different values -->
<field name="channel" type="string" indexed="true" stored="true" required="true" multiValued="false" />

<!-- 2 Possible values (PARENT\CHILD) -->
<field name="content_type" type="string" indexed="true" stored="true" required="true" multiValued="false" />

<!-- Cardinality of 1K values, document may have 0 to all possible values -->
<field name="groupIds" type="pint" indexed="true" stored="true" required="false" multiValued="true" />

<!-- Float value between -2 to 2, all documents have this field (applied for the below 3 fields) -->
<field name="min_score" type="pfloat" indexed="true" stored="true" required="false" multiValued="false" />
<field name="avg_score" type="pfloat" indexed="true" stored="true" required="false" multiValued="false" />
<field name="max_score" type="pfloat" indexed="true" stored="true" required="false" multiValued="false" />

<!-- Cardinality with about few thousands values, currently only 1 dynamic field exists with this prefix, document may have 1 to all possible values -->
<dynamicField name="Meta_is_*" type="pint" indexed="true" stored="true" multiValued="true" />


Any suggestions how to proceed with the investigation?

Right now we are trying to figure out if using single shard on each machine will help.
Artur Rudenko
Analytics Developer
Customer Engagement Solutions, VERINT
T +972.74.747.2536 | M +972.52.425.4686



This electronic message may contain proprietary and confidential information of Verint Systems Inc., its affiliates and/or subsidiaries. The information is intended to be for the use of the individual(s) or entity(ies) named above. If you are not the intended recipient (or authorized to receive this e-mail for the intended recipient), you may not use, copy, disclose or distribute to anyone this message or any information contained in this message. If you have received this electronic message in error, please notify us by replying to this e-mail.
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RE: Slow quires and facets

Rudenko, Artur
Promoting my question

Artur Rudenko

-----Original Message-----
From: Rudenko, Artur <[hidden email]>
Sent: Wednesday, February 12, 2020 10:33 PM
To: [hidden email]
Subject: Slow quires and facets

Hello everyone,
I'm am currently investigating a performance issue in our environment:
20M large PARENT documents and 800M nested small CHILD documents.
The system inserts about 400K PARENT documents and 16M CHILD documents per day. (Currently we stopped the calls insertion to investigate the performance issue) This is a solr cloud 8.3 environment with 7 servers (64 VCPU 128 GB RAM each, 24GB allocated to Solr) with single collection (32 shards and replication factor 2).

We experience generally slow queries (about 4-7 seconds) and facet times. The below query runs in about 14-16 seconds (we have to use limit:-1 due to a business case - cardinality is 1K values).

fq=channel:345133
&fq=content_type:PARENT
&fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total of int 562 values)
&q=*:*
&json.facet={
                "Chart_01_Bins":{
                                                type:terms,
                                                field:groupIds,
                                                mincount:1,
                                                limit:-1,
                                                numBuckets:true,
                                                missing:false,
                                                refine:true,
                                                facet:{
                                                                min_score_avg:"avg(min_score)",
                                                                max_score_avg:"avg(max_score)",
                                                                avg_score_avg:"avg(avg_score)"
                                                }
                },
                "Chart_01_FIELD_NOT_EXISTS":{
                                type:query,
                                q:"-groupIds:[* TO *]",
                                facet:{
                                                min_score_avg:"avg(min_score)",
                                                max_score_avg:"avg(max_score)",
                                                avg_score_avg:"avg(avg_score)"
                                }
                }
}
&rows=0

Also, when the facet is simplified, it takes about 4-6 seconds

fq=channel:345133
&fq=content_type:PARENT
&fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total of int 562 values)
&q=*:*
&json.facet={
                "Chart_01_Bins":{
                                type:terms,
                                field:groupIds,
                                mincount:1,
                                limit:-1,
                                numBuckets:true,
                                missing:false,
                                refine:true
                }
}
&rows=0

Schema relevant fields:

<fieldType name="pfloat" class="solr.FloatPointField" docValues="true"/> <fieldType name="pint" class="solr.IntPointField" docValues="true"/>

<!-- Currently only 1 value, in the future we expect to have about 25 different values --> <field name="channel" type="string" indexed="true" stored="true" required="true" multiValued="false" />

<!-- 2 Possible values (PARENT\CHILD) --> <field name="content_type" type="string" indexed="true" stored="true" required="true" multiValued="false" />

<!-- Cardinality of 1K values, document may have 0 to all possible values --> <field name="groupIds" type="pint" indexed="true" stored="true" required="false" multiValued="true" />

<!-- Float value between -2 to 2, all documents have this field (applied for the below 3 fields) --> <field name="min_score" type="pfloat" indexed="true" stored="true" required="false" multiValued="false" /> <field name="avg_score" type="pfloat" indexed="true" stored="true" required="false" multiValued="false" /> <field name="max_score" type="pfloat" indexed="true" stored="true" required="false" multiValued="false" />

<!-- Cardinality with about few thousands values, currently only 1 dynamic field exists with this prefix, document may have 1 to all possible values --> <dynamicField name="Meta_is_*" type="pint" indexed="true" stored="true" multiValued="true" />


Any suggestions how to proceed with the investigation?

Right now we are trying to figure out if using single shard on each machine will help.
Artur Rudenko
Analytics Developer
Customer Engagement Solutions, VERINT
T +972.74.747.2536 | M +972.52.425.4686



This electronic message may contain proprietary and confidential information of Verint Systems Inc., its affiliates and/or subsidiaries. The information is intended to be for the use of the individual(s) or entity(ies) named above. If you are not the intended recipient (or authorized to receive this e-mail for the intended recipient), you may not use, copy, disclose or distribute to anyone this message or any information contained in this message. If you have received this electronic message in error, please notify us by replying to this e-mail.


This electronic message may contain proprietary and confidential information of Verint Systems Inc., its affiliates and/or subsidiaries. The information is intended to be for the use of the individual(s) or entity(ies) named above. If you are not the intended recipient (or authorized to receive this e-mail for the intended recipient), you may not use, copy, disclose or distribute to anyone this message or any information contained in this message. If you have received this electronic message in error, please notify us by replying to this e-mail.
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Re: Slow quires and facets

Mikhail Khludnev-2
In reply to this post by Rudenko, Artur
I don't have any particular idea. Probably it's worth to start from
learning debugQuery=true output. There are caveats:
- it takes a while
- it's worth to limit shards to a few ones
- it used to produce incorrect json, and worked in only in wt=xml
At least it let to sneak something about the longest part of computation.
Few other thoughts: output with 1K entries doesn't seem like a regular
search engine response, usually results are scrolled with limit/offset, but
anyway it looks like analytical job for spark.


On Wed, Feb 12, 2020 at 11:32 PM Rudenko, Artur <[hidden email]>
wrote:

> Hello everyone,
> I'm am currently investigating a performance issue in our environment:
> 20M large PARENT documents and 800M nested small CHILD documents.
> The system inserts about 400K PARENT documents and 16M CHILD documents per
> day. (Currently we stopped the calls insertion to investigate the
> performance issue)
> This is a solr cloud 8.3 environment with 7 servers (64 VCPU 128 GB RAM
> each, 24GB allocated to Solr) with single collection (32 shards and
> replication factor 2).
>
> We experience generally slow queries (about 4-7 seconds) and facet times.
> The below query runs in about 14-16 seconds (we have to use limit:-1 due to
> a business case - cardinality is 1K values).
>
> fq=channel:345133
> &fq=content_type:PARENT
> &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total of
> int 562 values)
> &q=*:*
> &json.facet={
>                 "Chart_01_Bins":{
>                                                 type:terms,
>                                                 field:groupIds,
>                                                 mincount:1,
>                                                 limit:-1,
>                                                 numBuckets:true,
>                                                 missing:false,
>                                                 refine:true,
>                                                 facet:{
>
> min_score_avg:"avg(min_score)",
>
> max_score_avg:"avg(max_score)",
>
> avg_score_avg:"avg(avg_score)"
>                                                 }
>                 },
>                 "Chart_01_FIELD_NOT_EXISTS":{
>                                 type:query,
>                                 q:"-groupIds:[* TO *]",
>                                 facet:{
>
> min_score_avg:"avg(min_score)",
>
> max_score_avg:"avg(max_score)",
>
> avg_score_avg:"avg(avg_score)"
>                                 }
>                 }
> }
> &rows=0
>
> Also, when the facet is simplified, it takes about 4-6 seconds
>
> fq=channel:345133
> &fq=content_type:PARENT
> &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total of
> int 562 values)
> &q=*:*
> &json.facet={
>                 "Chart_01_Bins":{
>                                 type:terms,
>                                 field:groupIds,
>                                 mincount:1,
>                                 limit:-1,
>                                 numBuckets:true,
>                                 missing:false,
>                                 refine:true
>                 }
> }
> &rows=0
>
> Schema relevant fields:
>
> <fieldType name="pfloat" class="solr.FloatPointField" docValues="true"/>
> <fieldType name="pint" class="solr.IntPointField" docValues="true"/>
>
> <!-- Currently only 1 value, in the future we expect to have about 25
> different values -->
> <field name="channel" type="string" indexed="true" stored="true"
> required="true" multiValued="false" />
>
> <!-- 2 Possible values (PARENT\CHILD) -->
> <field name="content_type" type="string" indexed="true" stored="true"
> required="true" multiValued="false" />
>
> <!-- Cardinality of 1K values, document may have 0 to all possible values
> -->
> <field name="groupIds" type="pint" indexed="true" stored="true"
> required="false" multiValued="true" />
>
> <!-- Float value between -2 to 2, all documents have this field (applied
> for the below 3 fields) -->
> <field name="min_score" type="pfloat" indexed="true" stored="true"
> required="false" multiValued="false" />
> <field name="avg_score" type="pfloat" indexed="true" stored="true"
> required="false" multiValued="false" />
> <field name="max_score" type="pfloat" indexed="true" stored="true"
> required="false" multiValued="false" />
>
> <!-- Cardinality with about few thousands values, currently only 1 dynamic
> field exists with this prefix, document may have 1 to all possible values
> -->
> <dynamicField name="Meta_is_*" type="pint" indexed="true" stored="true"
> multiValued="true" />
>
>
> Any suggestions how to proceed with the investigation?
>
> Right now we are trying to figure out if using single shard on each
> machine will help.
> Artur Rudenko
> Analytics Developer
> Customer Engagement Solutions, VERINT
> T +972.74.747.2536 | M +972.52.425.4686
>
>
>
> This electronic message may contain proprietary and confidential
> information of Verint Systems Inc., its affiliates and/or subsidiaries. The
> information is intended to be for the use of the individual(s) or
> entity(ies) named above. If you are not the intended recipient (or
> authorized to receive this e-mail for the intended recipient), you may not
> use, copy, disclose or distribute to anyone this message or any information
> contained in this message. If you have received this electronic message in
> error, please notify us by replying to this e-mail.
>


--
Sincerely yours
Mikhail Khludnev
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RE: Slow quires and facets

Rudenko, Artur
Few updates:

The field below, each document has about 120 values. Currently the cardinality is 500 values.
<!-- Cardinality of 1K values, document may have 0 to all possible values -->
<field name="groupIds" type="pint" indexed="true" stored="true" required="false" multiValued="true" />

We removed the filter Meta_is_organizationIds to simplify the response (and it seems not to be the problem).
Also we set the limit only to 10 and set numBuckets:false and still we get 6.8 seconds responses (the previous query runs in about 14-16 seconds)


We also noticed that the field groupIds  is solr.IntPointField and according to Solr docs using TrieIntField might be faster:
https://lucene.apache.org/solr/guide/8_3/field-types-included-with-solr.html#field-types-included-with-solr

All Trie* numeric and date field types have been deprecated in favor of *Point field types. Point field types are better at range queries (speed, memory, disk), however simple field:value queries underperform relative to Trie. Either accept this, or continue to use Trie fields. This shortcoming may be addressed in a future release.

Do you think this might help?


We performed the below debug query in XML format as suggested:

<?xml version="1.0" encoding="UTF-8"?>
<response>
  <lst name="responseHeader">
    <bool name="zkConnected">true</bool>
    <int name="status">0</int>
    <int name="QTime">6808</int>
    <lst name="params">
      <str name="q">*:*</str>
      <str name="json.facet">{"Chart_01_Bins":{type:terms, field:groupIds, mincount:1, limit:10, numBuckets:false, missing:false, refine:true ,facet:{min_score_avg: "avg(min_score)",max_score_avg: "avg(max_score)",avg_score_avg: "avg(avg_score)"}},"Chart_01_FIELD_NOT_EXISTS": {type:query, q: "-groupIds:[* TO *]" ,facet:{min_score_avg: "avg(min_score)",max_score_avg: "avg(max_score)",avg_score_avg: "avg(avg_score)"}}}</str>
      <arr name="fq">
        <str>channel:345133</str>
        <str>content_type:PARENT</str>
      </arr>
      <str name="rows">0</str>
      <str name="wt">xml</str>
      <str name="debugQuery">true</str>
    </lst>
  </lst>
  <result name="response" numFound="20108328" start="0" maxScore="1.0"></result>
  <lst name="facets">
    <long name="count">20108328</long>
    <lst name="Chart_01_FIELD_NOT_EXISTS">
      <long name="count">24248</long>
      <double name="max_score_avg">0.0015258990432200593</double>
      <double name="avg_score_avg">-2.4744308808973936E-4</double>
      <double name="min_score_avg">-0.0012372154404486969</double>
    </lst>
    <lst name="Chart_01_Bins">
      <arr name="buckets">
        <lst>
          <int name="val">133000008</int>
          <long name="count">19766128</long>
          <double name="max_score_avg">1.0301153801720162</double>
          <double name="avg_score_avg">-0.016091049994686912</double>
          <double name="min_score_avg">-0.934160420207685</double>
        </lst>
        <lst>
          <int name="val">133000309</int>
          <long name="count">19678992</long>
          <double name="max_score_avg">1.027128905235771</double>
          <double name="avg_score_avg">-0.021377261229524585</double>
          <double name="min_score_avg">-0.9383299199656859</double>
        </lst>
        <lst>
          <int name="val">133000016</int>
          <long name="count">19586015</long>
          <double name="max_score_avg">1.0328805226198583</double>
          <double name="avg_score_avg">-0.021309381709827595</double>
          <double name="min_score_avg">-0.9431820282831003</double>
        </lst>
        <lst>
          <int name="val">133000326</int>
          <long name="count">18991262</long>
          <double name="max_score_avg">1.0590643252866423</double>
          <double name="avg_score_avg">-0.019758511191151334</double>
          <double name="min_score_avg">-0.9636441197805483</double>
        </lst>
        <lst>
          <int name="val">133000019</int>
          <long name="count">18888512</long>
          <double name="max_score_avg">1.0563612416377315</double>
          <double name="avg_score_avg">-0.024104479442487295</double>
          <double name="min_score_avg">-0.9688924575396817</double>
        </lst>
        <lst>
          <int name="val">133000020</int>
          <long name="count">18858046</long>
          <double name="max_score_avg">1.0675188347452709</double>
          <double name="avg_score_avg">-0.015537465871849449</double>
          <double name="min_score_avg">-0.9666198510676984</double>
        </lst>
        <lst>
          <int name="val">133000046</int>
          <long name="count">18854564</long>
          <double name="max_score_avg">1.0646018922402394</double>
          <double name="avg_score_avg">-0.01924574809063305</double>
          <double name="min_score_avg">-0.9673003731236052</double>
        </lst>
        <lst>
          <int name="val">133000173</int>
          <long name="count">18438355</long>
          <double name="max_score_avg">1.0699365758185304</double>
          <double name="avg_score_avg">-0.012621500507322752</double>
          <double name="min_score_avg">-0.9551372239401853</double>
        </lst>
        <lst>
          <int name="val">133000053</int>
          <long name="count">18280589</long>
          <double name="max_score_avg">1.07717860230237</double>
          <double name="avg_score_avg">-0.02438927275045303</double>
          <double name="min_score_avg">-0.9861261528306842</double>
        </lst>
        <lst>
          <int name="val">133000416</int>
          <long name="count">17905999</long>
          <double name="max_score_avg">1.0807140854212403</double>
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        <lst name="https://tas-ds-02.lab.local:8983/solr/0_shard25_replica_n98/">
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        <lst name="https://tas-ds-02.lab.local:8983/solr/0_shard11_replica_n42/">
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        <lst name="https://tas-ds-02.lab.local:8983/solr/0_shard22_replica_n84/">
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        <lst name="https://tas-ds-01.lab.local:8983/solr/0_shard12_replica_n44/">
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        <lst name="https://tas-ds-01.lab.local:8983/solr/0_shard5_replica_n16/">
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        <lst name="https://tas-ds-07.lab.local:8983/solr/0_shard6_replica_n22/">
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        <lst name="https://tas-ds-02.lab.local:8983/solr/0_shard29_replica_n112/">
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        <lst name="https://tas-ds-07.lab.local:8983/solr/0_shard13_replica_n50/">
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        <lst name="https://tas-ds-04.lab.local:8983/solr/0_shard19_replica_n74/">
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        <lst name="https://tas-ds-07.lab.local:8983/solr/0_shard27_replica_n106/">
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        <lst name="https://tas-ds-02.lab.local:8983/solr/0_shard8_replica_n28/">
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        <lst name="https://tas-ds-01.lab.local:8983/solr/0_shard26_replica_n100/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard17_replica_n66/">
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        <lst name="https://tas-ds-06.lab.local:8983/solr/0_shard9_replica_n34/">
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        <lst name="https://tas-ds-05.lab.local:8983/solr/0_shard18_replica_n68/">
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        <lst name="https://tas-ds-07.lab.local:8983/solr/0_shard20_replica_n78/">
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        <lst name="https://tas-ds-06.lab.local:8983/solr/0_shard23_replica_n90/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard21_replica_n80/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard28_replica_n108/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard3_replica_n10/">
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        <lst name="https://tas-ds-06.lab.local:8983/solr/0_shard30_replica_n118/">
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        <lst name="https://tas-ds-02.lab.local:8983/solr/0_shard4_replica_n14/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard24_replica_n94/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard14_replica_n52/">
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        <lst name="https://tas-ds-06.lab.local:8983/solr/0_shard2_replica_n6/">
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        <lst name="https://tas-ds-06.lab.local:8983/solr/0_shard16_replica_n62/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard10_replica_n38/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard31_replica_n122/">
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        <lst name="https://tas-ds-03.lab.local:8983/solr/0_shard7_replica_n24/">
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            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">629158</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4250</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">629058</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">19</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">629058</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4179</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628167</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">17</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628167</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4275</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">629527</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">18</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">629527</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4272</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628519</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">17</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628519</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4180</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">627138</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">17</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">627138</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4258</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628209</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">18</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628209</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4275</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">627933</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">17</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">627933</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4310</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628493</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">17</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628493</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4282</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628729</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">16</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628729</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4295</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">629268</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">14</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">629268</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4365</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628712</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">17</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628712</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4375</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">627799</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">16</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">627799</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4352</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628668</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">16</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628668</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4387</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">628893</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">16</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">628893</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4732</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">629159</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">18</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">629159</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4640</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">629017</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">1649</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">629017</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4734</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">627409</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">1647</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">627409</long>
        </lst>
        <lst>
          <str name="processor">FacetFieldProcessorByHashDV</str>
          <long name="elapse">4666</long>
          <str name="field">groupIds</str>
          <long name="limit">10</long>
          <long name="domainSize">626614</long>
          <long name="numBuckets">500</long>
        </lst>
        <lst>
          <str name="processor">FacetQueryProcessor</str>
          <long name="elapse">1822</long>
          <arr name="query">
            <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO 2147483647]</str>
          </arr>
          <long name="domainSize">626614</long>
        </lst>
      </arr>
    </lst>
    <lst name="json">
      <lst name="facet">
        <lst name="Chart_01_Bins">
          <str name="type">terms</str>
          <str name="field">groupIds</str>
          <long name="mincount">1</long>
          <long name="limit">10</long>
          <bool name="numBuckets">false</bool>
          <bool name="missing">false</bool>
          <bool name="refine">true</bool>
          <lst name="facet">
            <str name="min_score_avg">avg(min_score)</str>
            <str name="max_score_avg">avg(max_score)</str>
            <str name="avg_score_avg">avg(avg_score)</str>
          </lst>
        </lst>
        <lst name="Chart_01_FIELD_NOT_EXISTS">
          <str name="type">query</str>
          <str name="q">-groupIds:[* TO *]</str>
          <lst name="facet">
            <str name="min_score_avg">avg(min_score)</str>
            <str name="max_score_avg">avg(max_score)</str>
            <str name="avg_score_avg">avg(avg_score)</str>
          </lst>
        </lst>
      </lst>
    </lst>
    <lst name="timing">
      <double name="time">146588.0</double>
      <lst name="prepare">
        <double name="time">11.0</double>
        <lst name="query">
          <double name="time">0.0</double>
        </lst>
        <lst name="facet">
          <double name="time">0.0</double>
        </lst>
        <lst name="facet_module">
          <double name="time">9.0</double>
        </lst>
        <lst name="mlt">
          <double name="time">0.0</double>
        </lst>
        <lst name="highlight">
          <double name="time">0.0</double>
        </lst>
        <lst name="stats">
          <double name="time">0.0</double>
        </lst>
        <lst name="expand">
          <double name="time">0.0</double>
        </lst>
        <lst name="terms">
          <double name="time">0.0</double>
        </lst>
        <lst name="debug">
          <double name="time">0.0</double>
        </lst>
      </lst>
      <lst name="process">
        <double name="time">146537.0</double>
        <lst name="query">
          <double name="time">6150.0</double>
        </lst>
        <lst name="facet">
          <double name="time">0.0</double>
        </lst>
        <lst name="facet_module">
          <double name="time">140370.0</double>
        </lst>
        <lst name="mlt">
          <double name="time">0.0</double>
        </lst>
        <lst name="highlight">
          <double name="time">0.0</double>
        </lst>
        <lst name="stats">
          <double name="time">0.0</double>
        </lst>
        <lst name="expand">
          <double name="time">0.0</double>
        </lst>
        <lst name="terms">
          <double name="time">0.0</double>
        </lst>
        <lst name="debug">
          <double name="time">0.0</double>
        </lst>
      </lst>
    </lst>
    <str name="rawquerystring">*:*</str>
    <str name="querystring">*:*</str>
    <str name="parsedquery">MatchAllDocsQuery(*:*)</str>
    <str name="parsedquery_toString">*:*</str>
    <str name="QParser">LuceneQParser</str>
    <lst name="explain"/></lst>
</response>


Artur Rudenko
-----Original Message-----
From: Mikhail Khludnev <[hidden email]>
Sent: Saturday, February 15, 2020 8:44 PM
To: solr-user <[hidden email]>
Subject: Re: Slow quires and facets

I don't have any particular idea. Probably it's worth to start from learning debugQuery=true output. There are caveats:
- it takes a while
- it's worth to limit shards to a few ones
- it used to produce incorrect json, and worked in only in wt=xml At least it let to sneak something about the longest part of computation.
Few other thoughts: output with 1K entries doesn't seem like a regular search engine response, usually results are scrolled with limit/offset, but anyway it looks like analytical job for spark.


On Wed, Feb 12, 2020 at 11:32 PM Rudenko, Artur <[hidden email]>
wrote:

> Hello everyone,
> I'm am currently investigating a performance issue in our environment:
> 20M large PARENT documents and 800M nested small CHILD documents.
> The system inserts about 400K PARENT documents and 16M CHILD documents
> per day. (Currently we stopped the calls insertion to investigate the
> performance issue) This is a solr cloud 8.3 environment with 7 servers
> (64 VCPU 128 GB RAM each, 24GB allocated to Solr) with single
> collection (32 shards and replication factor 2).
>
> We experience generally slow queries (about 4-7 seconds) and facet times.
> The below query runs in about 14-16 seconds (we have to use limit:-1
> due to a business case - cardinality is 1K values).
>
> fq=channel:345133
> &fq=content_type:PARENT
> &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total
> of int 562 values)
> &q=*:*
> &json.facet={
>                 "Chart_01_Bins":{
>                                                 type:terms,
>                                                 field:groupIds,
>                                                 mincount:1,
>                                                 limit:-1,
>                                                 numBuckets:true,
>                                                 missing:false,
>                                                 refine:true,
>                                                 facet:{
>
> min_score_avg:"avg(min_score)",
>
> max_score_avg:"avg(max_score)",
>
> avg_score_avg:"avg(avg_score)"
>                                                 }
>                 },
>                 "Chart_01_FIELD_NOT_EXISTS":{
>                                 type:query,
>                                 q:"-groupIds:[* TO *]",
>                                 facet:{
>
> min_score_avg:"avg(min_score)",
>
> max_score_avg:"avg(max_score)",
>
> avg_score_avg:"avg(avg_score)"
>                                 }
>                 }
> }
> &rows=0
>
> Also, when the facet is simplified, it takes about 4-6 seconds
>
> fq=channel:345133
> &fq=content_type:PARENT
> &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total
> of int 562 values)
> &q=*:*
> &json.facet={
>                 "Chart_01_Bins":{
>                                 type:terms,
>                                 field:groupIds,
>                                 mincount:1,
>                                 limit:-1,
>                                 numBuckets:true,
>                                 missing:false,
>                                 refine:true
>                 }
> }
> &rows=0
>
> Schema relevant fields:
>
> <fieldType name="pfloat" class="solr.FloatPointField"
> docValues="true"/> <fieldType name="pint" class="solr.IntPointField"
> docValues="true"/>
>
> <!-- Currently only 1 value, in the future we expect to have about 25
> different values --> <field name="channel" type="string"
> indexed="true" stored="true"
> required="true" multiValued="false" />
>
> <!-- 2 Possible values (PARENT\CHILD) --> <field name="content_type"
> type="string" indexed="true" stored="true"
> required="true" multiValued="false" />
>
> <!-- Cardinality of 1K values, document may have 0 to all possible
> values
> -->
> <field name="groupIds" type="pint" indexed="true" stored="true"
> required="false" multiValued="true" />
>
> <!-- Float value between -2 to 2, all documents have this field
> (applied for the below 3 fields) --> <field name="min_score"
> type="pfloat" indexed="true" stored="true"
> required="false" multiValued="false" /> <field name="avg_score"
> type="pfloat" indexed="true" stored="true"
> required="false" multiValued="false" /> <field name="max_score"
> type="pfloat" indexed="true" stored="true"
> required="false" multiValued="false" />
>
> <!-- Cardinality with about few thousands values, currently only 1
> dynamic field exists with this prefix, document may have 1 to all
> possible values
> -->
> <dynamicField name="Meta_is_*" type="pint" indexed="true" stored="true"
> multiValued="true" />
>
>
> Any suggestions how to proceed with the investigation?
>
> Right now we are trying to figure out if using single shard on each
> machine will help.
> Artur Rudenko
> Analytics Developer
> Customer Engagement Solutions, VERINT
> T +972.74.747.2536 | M +972.52.425.4686
>
>
>
> This electronic message may contain proprietary and confidential
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> subsidiaries. The information is intended to be for the use of the
> individual(s) or
> entity(ies) named above. If you are not the intended recipient (or
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> information contained in this message. If you have received this
> electronic message in error, please notify us by replying to this e-mail.
>


--
Sincerely yours
Mikhail Khludnev


This electronic message may contain proprietary and confidential information of Verint Systems Inc., its affiliates and/or subsidiaries. The information is intended to be for the use of the individual(s) or entity(ies) named above. If you are not the intended recipient (or authorized to receive this e-mail for the intended recipient), you may not use, copy, disclose or distribute to anyone this message or any information contained in this message. If you have received this electronic message in error, please notify us by replying to this e-mail.
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Re: Slow quires and facets

Mikhail Khludnev-2
Hello,
It's still not clear. Ideally it's worth to look at code execution sampling
(a kind of profiling). Since here we evidence seconds of processing, even
looking at thread dumps in SolrAdmin or via REST api , or jstack can give a
clue about hotspot.
Few ideas:
- it's worth to  disable refining for experiments, it might be expensive
- now event it's limited by 10, it sort by counts, that require to count
all buckets, so, if limit:-1 is prohibitive, one may try sort buckets "by
index".
- another idea is experiment with prefix to limit processing amount, just
for beginning.
- giving that cardinality is not huge DVhash might be suboptimal,
experimenting with different methods might get some gain.
- what I remember is limit:-1 might process in single pass, but limit>0
trigger two stage processing: counting buckets, then picking per bucket
docsets and calc sub-stats.
- giving that every bucket has a big count, averages might be calculated on
smaller set samples: groupId field facet might have query subfacet yielding
semi-random docset sample (a part of), and then averages might be counted
on it. It's even better for stats since it cuts off long tails.
Enjoy.

On Wed, Feb 19, 2020 at 4:29 PM Rudenko, Artur <[hidden email]>
wrote:

> Few updates:
>
> The field below, each document has about 120 values. Currently the
> cardinality is 500 values.
> <!-- Cardinality of 1K values, document may have 0 to all possible values
> -->
> <field name="groupIds" type="pint" indexed="true" stored="true"
> required="false" multiValued="true" />
>
> We removed the filter Meta_is_organizationIds to simplify the response
> (and it seems not to be the problem).
> Also we set the limit only to 10 and set numBuckets:false and still we get
> 6.8 seconds responses (the previous query runs in about 14-16 seconds)
>
>
> We also noticed that the field groupIds  is solr.IntPointField and
> according to Solr docs using TrieIntField might be faster:
>
> https://lucene.apache.org/solr/guide/8_3/field-types-included-with-solr.html#field-types-included-with-solr
>
> All Trie* numeric and date field types have been deprecated in favor of
> *Point field types. Point field types are better at range queries (speed,
> memory, disk), however simple field:value queries underperform relative to
> Trie. Either accept this, or continue to use Trie fields. This shortcoming
> may be addressed in a future release.
>
> Do you think this might help?
>
>
> We performed the below debug query in XML format as suggested:
>
> <?xml version="1.0" encoding="UTF-8"?>
> <response>
>   <lst name="responseHeader">
>     <bool name="zkConnected">true</bool>
>     <int name="status">0</int>
>     <int name="QTime">6808</int>
>     <lst name="params">
>       <str name="q">*:*</str>
>       <str name="json.facet">{"Chart_01_Bins":{type:terms, field:groupIds,
> mincount:1, limit:10, numBuckets:false, missing:false, refine:true
> ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}},"Chart_01_FIELD_NOT_EXISTS": {type:query, q:
> "-groupIds:[* TO *]" ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg: "avg(avg_score)"}}}</str>
>       <arr name="fq">
>         <str>channel:345133</str>
>         <str>content_type:PARENT</str>
>       </arr>
>       <str name="rows">0</str>
>       <str name="wt">xml</str>
>       <str name="debugQuery">true</str>
>     </lst>
>   </lst>
>   <result name="response" numFound="20108328" start="0"
> maxScore="1.0"></result>
>   <lst name="facets">
>     <long name="count">20108328</long>
>     <lst name="Chart_01_FIELD_NOT_EXISTS">
>       <long name="count">24248</long>
>       <double name="max_score_avg">0.0015258990432200593</double>
>       <double name="avg_score_avg">-2.4744308808973936E-4</double>
>       <double name="min_score_avg">-0.0012372154404486969</double>
>     </lst>
>     <lst name="Chart_01_Bins">
>       <arr name="buckets">
>         <lst>
>           <int name="val">133000008</int>
>           <long name="count">19766128</long>
>           <double name="max_score_avg">1.0301153801720162</double>
>           <double name="avg_score_avg">-0.016091049994686912</double>
>           <double name="min_score_avg">-0.934160420207685</double>
>         </lst>
>         <lst>
>           <int name="val">133000309</int>
>           <long name="count">19678992</long>
>           <double name="max_score_avg">1.027128905235771</double>
>           <double name="avg_score_avg">-0.021377261229524585</double>
>           <double name="min_score_avg">-0.9383299199656859</double>
>         </lst>
>         <lst>
>           <int name="val">133000016</int>
>           <long name="count">19586015</long>
>           <double name="max_score_avg">1.0328805226198583</double>
>           <double name="avg_score_avg">-0.021309381709827595</double>
>           <double name="min_score_avg">-0.9431820282831003</double>
>         </lst>
>         <lst>
>           <int name="val">133000326</int>
>           <long name="count">18991262</long>
>           <double name="max_score_avg">1.0590643252866423</double>
>           <double name="avg_score_avg">-0.019758511191151334</double>
>           <double name="min_score_avg">-0.9636441197805483</double>
>         </lst>
>         <lst>
>           <int name="val">133000019</int>
>           <long name="count">18888512</long>
>           <double name="max_score_avg">1.0563612416377315</double>
>           <double name="avg_score_avg">-0.024104479442487295</double>
>           <double name="min_score_avg">-0.9688924575396817</double>
>         </lst>
>         <lst>
>           <int name="val">133000020</int>
>           <long name="count">18858046</long>
>           <double name="max_score_avg">1.0675188347452709</double>
>           <double name="avg_score_avg">-0.015537465871849449</double>
>           <double name="min_score_avg">-0.9666198510676984</double>
>         </lst>
>         <lst>
>           <int name="val">133000046</int>
>           <long name="count">18854564</long>
>           <double name="max_score_avg">1.0646018922402394</double>
>           <double name="avg_score_avg">-0.01924574809063305</double>
>           <double name="min_score_avg">-0.9673003731236052</double>
>         </lst>
>         <lst>
>           <int name="val">133000173</int>
>           <long name="count">18438355</long>
>           <double name="max_score_avg">1.0699365758185304</double>
>           <double name="avg_score_avg">-0.012621500507322752</double>
>           <double name="min_score_avg">-0.9551372239401853</double>
>         </lst>
>         <lst>
>           <int name="val">133000053</int>
>           <long name="count">18280589</long>
>           <double name="max_score_avg">1.07717860230237</double>
>           <double name="avg_score_avg">-0.02438927275045303</double>
>           <double name="min_score_avg">-0.9861261528306842</double>
>         </lst>
>         <lst>
>           <int name="val">133000416</int>
>           <long name="count">17905999</long>
>           <double name="max_score_avg">1.0807140854212403</double>
>           <double name="avg_score_avg">-0.02857962204396297</double>
>           <double name="min_score_avg">-0.9941415030935342</double>
>         </lst>
>       </arr>
>     </lst>
>   </lst>
>   <lst name="debug">
>     <lst name="track">
>       <str
> name="rid">tas-ds-01.lab.local-0_shard12_replica_n44-1582040461716-15</str>
>       <lst name="EXECUTE_QUERY">
>         <lst name="
> https://tas-ds-02.lab.local:8983/solr/0_shard32_replica_n126/">
>           <str name="QTime">3893</str>
>           <str name="ElapsedTime">3905</str>
>           <str name="RequestPurpose">GET_TOP_IDS,SET_TERM_STATS</str>
>           <str name="NumFound">629250</str>
>           <str
> name="Response">{responseHeader={zkConnected=true,status=0,QTime=3893,params={df=text_en,distrib=false,debug=[false,
> timing, track],_facet_={},fl=[id,
> score],shards.purpose=1064964,hl.fragsize=100000,start=0,fsv=true,fq=[channel:345133,
> content_type:PARENT],shard.url=
> https://tas-ds-02.lab.local:8983/solr/0_shard32_replica_n126/,rows=0,rid=tas-ds-01.lab.local-0_shard12_replica_n44-1582040461716-15,version=2,q=*:*,json.facet={"Chart_01_Bins":{type:terms,
> field:groupIds, mincount:1, limit:10, numBuckets:false, missing:false,
> refine:true ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}},"Chart_01_FIELD_NOT_EXISTS": {type:query, q:
> "-groupIds:[* TO *]" ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}}},hl.maxAnalyzedChars=100000,omitHeader=false,requestPurpose=GET_TOP_IDS,SET_TERM_STATS,NOW=1582040461715,isShard=true,wt=javabin,debugQuery=false}},response={numFound=629250,start=0,maxScore=1.0,docs=[]},sort_values={},facets={count=629250,Chart_01_Bins={buckets=[{val=133000008,count=618452,min_score_avg=[618452,
> -576939.2808909193],max_score_avg=[618452,
> 637080.180480836],avg_score_avg=[618452, -9495.009733909965]},
> {val=133000309,count=615672,min_score_avg=[615672,
> -576887.1264572814],max_score_avg=[615672,
> 632536.9241082799],avg_score_avg=[615672, -12578.154329540432]},
> {val=133000016,count=612702,min_score_avg=[612702,
> -577158.9922628701],max_score_avg=[612702,
> 633075.5110024717],avg_score_avg=[612702, -12495.717564551383]},
> {val=133000326,count=593872,min_score_avg=[593872,
> -571770.8389462605],max_score_avg=[593872,
> 629157.2776536848],avg_score_avg=[593872, -11311.731255522345]},
> {val=133000019,count=590811,min_score_avg=[590811,
> -571962.5987144224],max_score_avg=[590811,
> 624241.8250667024],avg_score_avg=[590811, -13848.260609685289]},
> {val=133000020,count=589758,min_score_avg=[589758,
> -569468.3429295402],max_score_avg=[589758,
> 629863.7633762769],avg_score_avg=[589758, -8692.508232006314]},
> {val=133000046,count=589574,min_score_avg=[589574,
> -569800.0024026707],max_score_avg=[589574,
> 627875.5197924953],avg_score_avg=[589574, -10939.054679468622]},
> {val=133000173,count=576678,min_score_avg=[576678,
> -550264.2602007724],max_score_avg=[576678,
> 617409.7981856186],avg_score_avg=[576678, -6746.609781782537]},
> {val=133000053,count=571685,min_score_avg=[571685,
> -563236.478021916],max_score_avg=[571685,
> 616242.1556677315],avg_score_avg=[571685, -13436.449740949536]},
> {val=133000416,count=560236,min_score_avg=[560236,
> -556272.329609137],max_score_avg=[560236,
> 605500.300901534],avg_score_avg=[560236, -15580.028122156318]},
> {val=133000426,count=555083,min_score_avg=[555083,
> -546965.7124627493],max_score_avg=[555083,
> 606410.2503346],avg_score_avg=[555083, -10241.202538815398]},
> {val=133000319,count=554782,min_score_avg=[554782,
> -552676.7978098113],max_score_avg=[554782,
> 606736.6013785154],avg_score_avg=[554782, -12885.897277893406]},
> {val=133000419,count=536395,min_score_avg=[536395,
> -535177.826233197],max_score_avg=[536395,
> 594359.362744743],avg_score_avg=[536395, -10421.214047468386]},
> {val=133000158,count=529741,min_score_avg=[529741,
> -543754.5367996339],max_score_avg=[529741,
> 586494.3649332896],avg_score_avg=[529741, -18286.315407010617]},
> {val=133000014,count=527716,min_score_avg=[527716,
> -531158.8040696923],max_score_avg=[527716,
> 583973.0706529561],avg_score_avg=[527716,
> -12620.502557002552]}],more=true},Chart_01_FIELD_NOT_EXISTS={count=808,min_score_avg=[808,
> -2.0],max_score_avg=[808, 3.0],avg_score_avg=[808,
> 0.0]}},debug={facet-trace={processor=FacetQueryProcessor,elapse=3713,query=null,domainSize=629250,sub-facet=[{processor=FacetFieldProcessorByHashDV,elapse=3699,field=groupIds,limit=10,domainSize=629250,numBuckets=500},
> {processor=FacetQueryProcessor,elapse=14,query=[org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648
> TO
> 2147483647]],domainSize=629250}]},json={facet={Chart_01_Bins={type=terms,
> field=groupIds, mincount=1, limit=10, numBuckets=false, missing=false,
> refine=true, facet={min_score_avg=avg(min_score),
> max_score_avg=avg(max_score), avg_score_avg=avg(avg_score)}},
> Chart_01_FIELD_NOT_EXISTS={type=query, q=-groupIds:[* TO *],
> facet={min_score_avg=avg(min_score), max_score_avg=avg(max_score),
> avg_score_avg=avg(avg_score)}}}},timing={time=3893.0,prepare={time=0.0,query={time=0.0},facet={time=0.0},facet_module={time=0.0},mlt={time=0.0},highlight={time=0.0},stats={time=0.0},expand={time=0.0},terms={time=0.0},debug={time=0.0}},process={time=3892.0,query={time=178.0},facet={time=0.0},facet_module={time=3714.0},mlt={time=0.0},highlight={time=0.0},stats={time=0.0},expand={time=0.0},terms={time=0.0},debug={time=0.0}}}}}</str>
>         </lst>
>         <lst name="
> https://tas-ds-02.lab.local:8983/solr/0_shard25_replica_n98/">
>          <str name="QTime">3969</str>
>           <str name="ElapsedTime">3996</str>
>           <str name="RequestPurpose">GET_TOP_IDS,SET_TERM_STATS</str>
>           <str name="NumFound">627650</str>
>           <str
> name="Response">{responseHeader={zkConnected=true,status=0,QTime=3969,params={df=text_en,distrib=false,debug=[false,
> timing, track],_facet_={},fl=[id,
> score],shards.purpose=1064964,hl.fragsize=100000,start=0,fsv=true,fq=[channel:345133,
> content_type:PARENT],shard.url=
> https://tas-ds-02.lab.local:8983/solr/0_shard25_replica_n98/,rows=0,rid=tas-ds-01.lab.local-0_shard12_replica_n44-1582040461716-15,version=2,q=*:*,json.facet={"Chart_01_Bins":{type:terms,
> field:groupIds, mincount:1, limit:10, numBuckets:false, missing:false,
> refine:true ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}},"Chart_01_FIELD_NOT_EXISTS": {type:query, q:
> "-groupIds:[* TO *]" ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}}},hl.maxAnalyzedChars=100000,omitHeader=false,requestPurpose=GET_TOP_IDS,SET_TERM_STATS,NOW=1582040461715,isShard=true,wt=javabin,debugQuery=false}},response={numFound=627650,start=0,maxScore=1.0,docs=[]},sort_values={},facets={count=627650,Chart_01_Bins={buckets=[{val=133000008,count=616999,min_score_avg=[616999,
> -577215.092938982],max_score_avg=[616999,
> 636068.6822010912],avg_score_avg=[616999, -9888.548473187637]},
> {val=133000309,count=614159,min_score_avg=[614159,
> -577291.6011139303],max_score_avg=[614159,
> 631383.874547679],avg_score_avg=[614159, -13155.474374183364]},
> {val=133000016,count=611386,min_score_avg=[611386,
> -577500.5835904554],max_score_avg=[611386,
> 632022.606553603],avg_score_avg=[611386, -12925.144421216943]},
> {val=133000326,count=592870,min_score_avg=[592870,
> -572183.4784369543],max_score_avg=[592870,
> 628371.8541558869],avg_score_avg=[592870, -11662.493946856495]},
> {val=133000019,count=589777,min_score_avg=[589777,
> -572138.3667944632],max_score_avg=[589777,
> 623394.8917776607],avg_score_avg=[589777, -14117.572841084142]},
> {val=133000046,count=588591,min_score_avg=[588591,
> -570194.2330829725],max_score_avg=[588591,
> 627170.3702051006],avg_score_avg=[588591, -11239.333427489411]},
> {val=133000020,count=588580,min_score_avg=[588580,
> -569880.7511399835],max_score_avg=[588580,
> 628833.8944486603],avg_score_avg=[588580, -9101.130680490956]},
> {val=133000173,count=575488,min_score_avg=[575488,
> -550518.6634891294],max_score_avg=[575488,
> 616335.7149619758],avg_score_avg=[575488, -7180.014344083388]},
> {val=133000053,count=570884,min_score_avg=[570884,
> -563861.0909794196],max_score_avg=[570884,
> 615363.9106183592],avg_score_avg=[570884, -13924.756814880138]},
> {val=133000416,count=558904,min_score_avg=[558904,
> -556365.0997987613],max_score_avg=[558904,
> 604397.6927064024],avg_score_avg=[558904, -15819.343027989922]},
> {val=133000426,count=554345,min_score_avg=[554345,
> -547577.5947113298],max_score_avg=[554345,
> 605668.3820153959],avg_score_avg=[554345, -10689.879367479542]},
> {val=133000319,count=553978,min_score_avg=[553978,
> -553089.8339664321],max_score_avg=[553978,
> 605896.3165234756],avg_score_avg=[553978, -13287.287667892488]},
> {val=133000419,count=535468,min_score_avg=[535468,
> -535588.4850753751],max_score_avg=[535468,
> 593726.2633218896],avg_score_avg=[535468, -10738.243916065556]},
> {val=133000158,count=528248,min_score_avg=[528248,
> -543609.1260265261],max_score_avg=[528248,
> 585328.6052017678],avg_score_avg=[528248, -18435.08836668043]},
> {val=133000014,count=526373,min_score_avg=[526373,
> -530742.4324899539],max_score_avg=[526373,
> 583106.5033674445],avg_score_avg=[526373,
> -12690.486354421499]}],more=true},Chart_01_FIELD_NOT_EXISTS={count=767,min_score_avg=[767,
> 0.0],max_score_avg=[767, 0.0],avg_score_avg=[767,
> 0.0]}},debug={facet-trace={processor=FacetQueryProcessor,elapse=3814,query=null,domainSize=627650,sub-facet=[{processor=FacetFieldProcessorByHashDV,elapse=3799,field=groupIds,limit=10,domainSize=627650,numBuckets=500},
> {processor=FacetQueryProcessor,elapse=14,query=[org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648
> TO
> 2147483647]],domainSize=627650}]},json={facet={Chart_01_Bins={type=terms,
> field=groupIds, mincount=1, limit=10, numBuckets=false, missing=false,
> refine=true, facet={min_score_avg=avg(min_score),
> max_score_avg=avg(max_score), avg_score_avg=avg(avg_score)}},
> Chart_01_FIELD_NOT_EXISTS={type=query, q=-groupIds:[* TO *],
> facet={min_score_avg=avg(min_score), max_score_avg=avg(max_score),
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>           <long name="limit">10</long>
>           <long name="domainSize">626614</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">1822</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">626614</long>
>         </lst>
>       </arr>
>     </lst>
>     <lst name="json">
>       <lst name="facet">
>         <lst name="Chart_01_Bins">
>           <str name="type">terms</str>
>           <str name="field">groupIds</str>
>           <long name="mincount">1</long>
>           <long name="limit">10</long>
>           <bool name="numBuckets">false</bool>
>           <bool name="missing">false</bool>
>           <bool name="refine">true</bool>
>           <lst name="facet">
>             <str name="min_score_avg">avg(min_score)</str>
>             <str name="max_score_avg">avg(max_score)</str>
>             <str name="avg_score_avg">avg(avg_score)</str>
>           </lst>
>         </lst>
>         <lst name="Chart_01_FIELD_NOT_EXISTS">
>           <str name="type">query</str>
>           <str name="q">-groupIds:[* TO *]</str>
>           <lst name="facet">
>             <str name="min_score_avg">avg(min_score)</str>
>             <str name="max_score_avg">avg(max_score)</str>
>             <str name="avg_score_avg">avg(avg_score)</str>
>           </lst>
>         </lst>
>       </lst>
>     </lst>
>     <lst name="timing">
>       <double name="time">146588.0</double>
>       <lst name="prepare">
>         <double name="time">11.0</double>
>         <lst name="query">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="facet">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="facet_module">
>           <double name="time">9.0</double>
>         </lst>
>         <lst name="mlt">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="highlight">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="stats">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="expand">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="terms">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="debug">
>           <double name="time">0.0</double>
>         </lst>
>       </lst>
>       <lst name="process">
>         <double name="time">146537.0</double>
>         <lst name="query">
>           <double name="time">6150.0</double>
>         </lst>
>         <lst name="facet">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="facet_module">
>           <double name="time">140370.0</double>
>         </lst>
>         <lst name="mlt">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="highlight">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="stats">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="expand">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="terms">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="debug">
>           <double name="time">0.0</double>
>         </lst>
>       </lst>
>     </lst>
>     <str name="rawquerystring">*:*</str>
>     <str name="querystring">*:*</str>
>     <str name="parsedquery">MatchAllDocsQuery(*:*)</str>
>     <str name="parsedquery_toString">*:*</str>
>     <str name="QParser">LuceneQParser</str>
>     <lst name="explain"/></lst>
> </response>
>
>
> Artur Rudenko
> -----Original Message-----
> From: Mikhail Khludnev <[hidden email]>
> Sent: Saturday, February 15, 2020 8:44 PM
> To: solr-user <[hidden email]>
> Subject: Re: Slow quires and facets
>
> I don't have any particular idea. Probably it's worth to start from
> learning debugQuery=true output. There are caveats:
> - it takes a while
> - it's worth to limit shards to a few ones
> - it used to produce incorrect json, and worked in only in wt=xml At least
> it let to sneak something about the longest part of computation.
> Few other thoughts: output with 1K entries doesn't seem like a regular
> search engine response, usually results are scrolled with limit/offset, but
> anyway it looks like analytical job for spark.
>
>
> On Wed, Feb 12, 2020 at 11:32 PM Rudenko, Artur <[hidden email]>
> wrote:
>
> > Hello everyone,
> > I'm am currently investigating a performance issue in our environment:
> > 20M large PARENT documents and 800M nested small CHILD documents.
> > The system inserts about 400K PARENT documents and 16M CHILD documents
> > per day. (Currently we stopped the calls insertion to investigate the
> > performance issue) This is a solr cloud 8.3 environment with 7 servers
> > (64 VCPU 128 GB RAM each, 24GB allocated to Solr) with single
> > collection (32 shards and replication factor 2).
> >
> > We experience generally slow queries (about 4-7 seconds) and facet times.
> > The below query runs in about 14-16 seconds (we have to use limit:-1
> > due to a business case - cardinality is 1K values).
> >
> > fq=channel:345133
> > &fq=content_type:PARENT
> > &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total
> > of int 562 values)
> > &q=*:*
> > &json.facet={
> >                 "Chart_01_Bins":{
> >                                                 type:terms,
> >                                                 field:groupIds,
> >                                                 mincount:1,
> >                                                 limit:-1,
> >                                                 numBuckets:true,
> >                                                 missing:false,
> >                                                 refine:true,
> >                                                 facet:{
> >
> > min_score_avg:"avg(min_score)",
> >
> > max_score_avg:"avg(max_score)",
> >
> > avg_score_avg:"avg(avg_score)"
> >                                                 }
> >                 },
> >                 "Chart_01_FIELD_NOT_EXISTS":{
> >                                 type:query,
> >                                 q:"-groupIds:[* TO *]",
> >                                 facet:{
> >
> > min_score_avg:"avg(min_score)",
> >
> > max_score_avg:"avg(max_score)",
> >
> > avg_score_avg:"avg(avg_score)"
> >                                 }
> >                 }
> > }
> > &rows=0
> >
> > Also, when the facet is simplified, it takes about 4-6 seconds
> >
> > fq=channel:345133
> > &fq=content_type:PARENT
> > &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total
> > of int 562 values)
> > &q=*:*
> > &json.facet={
> >                 "Chart_01_Bins":{
> >                                 type:terms,
> >                                 field:groupIds,
> >                                 mincount:1,
> >                                 limit:-1,
> >                                 numBuckets:true,
> >                                 missing:false,
> >                                 refine:true
> >                 }
> > }
> > &rows=0
> >
> > Schema relevant fields:
> >
> > <fieldType name="pfloat" class="solr.FloatPointField"
> > docValues="true"/> <fieldType name="pint" class="solr.IntPointField"
> > docValues="true"/>
> >
> > <!-- Currently only 1 value, in the future we expect to have about 25
> > different values --> <field name="channel" type="string"
> > indexed="true" stored="true"
> > required="true" multiValued="false" />
> >
> > <!-- 2 Possible values (PARENT\CHILD) --> <field name="content_type"
> > type="string" indexed="true" stored="true"
> > required="true" multiValued="false" />
> >
> > <!-- Cardinality of 1K values, document may have 0 to all possible
> > values
> > -->
> > <field name="groupIds" type="pint" indexed="true" stored="true"
> > required="false" multiValued="true" />
> >
> > <!-- Float value between -2 to 2, all documents have this field
> > (applied for the below 3 fields) --> <field name="min_score"
> > type="pfloat" indexed="true" stored="true"
> > required="false" multiValued="false" /> <field name="avg_score"
> > type="pfloat" indexed="true" stored="true"
> > required="false" multiValued="false" /> <field name="max_score"
> > type="pfloat" indexed="true" stored="true"
> > required="false" multiValued="false" />
> >
> > <!-- Cardinality with about few thousands values, currently only 1
> > dynamic field exists with this prefix, document may have 1 to all
> > possible values
> > -->
> > <dynamicField name="Meta_is_*" type="pint" indexed="true" stored="true"
> > multiValued="true" />
> >
> >
> > Any suggestions how to proceed with the investigation?
> >
> > Right now we are trying to figure out if using single shard on each
> > machine will help.
> > Artur Rudenko
> > Analytics Developer
> > Customer Engagement Solutions, VERINT
> > T +972.74.747.2536 | M +972.52.425.4686
> >
> >
> >
> > This electronic message may contain proprietary and confidential
> > information of Verint Systems Inc., its affiliates and/or
> > subsidiaries. The information is intended to be for the use of the
> > individual(s) or
> > entity(ies) named above. If you are not the intended recipient (or
> > authorized to receive this e-mail for the intended recipient), you may
> > not use, copy, disclose or distribute to anyone this message or any
> > information contained in this message. If you have received this
> > electronic message in error, please notify us by replying to this e-mail.
> >
>
>
> --
> Sincerely yours
> Mikhail Khludnev
>
>
> This electronic message may contain proprietary and confidential
> information of Verint Systems Inc., its affiliates and/or subsidiaries. The
> information is intended to be for the use of the individual(s) or
> entity(ies) named above. If you are not the intended recipient (or
> authorized to receive this e-mail for the intended recipient), you may not
> use, copy, disclose or distribute to anyone this message or any information
> contained in this message. If you have received this electronic message in
> error, please notify us by replying to this e-mail.
>


--
Sincerely yours
Mikhail Khludnev
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Re: Slow quires and facets

Mikhail Khludnev-2
In reply to this post by Rudenko, Artur
Fwiw, it seems like  Chart_01_FIELD_NOT_EXISTS might be implemented via
"missing" property of terms facet.

On Wed, Feb 19, 2020 at 4:29 PM Rudenko, Artur <[hidden email]>
wrote:

> Few updates:
>
> The field below, each document has about 120 values. Currently the
> cardinality is 500 values.
> <!-- Cardinality of 1K values, document may have 0 to all possible values
> -->
> <field name="groupIds" type="pint" indexed="true" stored="true"
> required="false" multiValued="true" />
>
> We removed the filter Meta_is_organizationIds to simplify the response
> (and it seems not to be the problem).
> Also we set the limit only to 10 and set numBuckets:false and still we get
> 6.8 seconds responses (the previous query runs in about 14-16 seconds)
>
>
> We also noticed that the field groupIds  is solr.IntPointField and
> according to Solr docs using TrieIntField might be faster:
>
> https://lucene.apache.org/solr/guide/8_3/field-types-included-with-solr.html#field-types-included-with-solr
>
> All Trie* numeric and date field types have been deprecated in favor of
> *Point field types. Point field types are better at range queries (speed,
> memory, disk), however simple field:value queries underperform relative to
> Trie. Either accept this, or continue to use Trie fields. This shortcoming
> may be addressed in a future release.
>
> Do you think this might help?
>
>
> We performed the below debug query in XML format as suggested:
>
> <?xml version="1.0" encoding="UTF-8"?>
> <response>
>   <lst name="responseHeader">
>     <bool name="zkConnected">true</bool>
>     <int name="status">0</int>
>     <int name="QTime">6808</int>
>     <lst name="params">
>       <str name="q">*:*</str>
>       <str name="json.facet">{"Chart_01_Bins":{type:terms, field:groupIds,
> mincount:1, limit:10, numBuckets:false, missing:false, refine:true
> ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}},"Chart_01_FIELD_NOT_EXISTS": {type:query, q:
> "-groupIds:[* TO *]" ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg: "avg(avg_score)"}}}</str>
>       <arr name="fq">
>         <str>channel:345133</str>
>         <str>content_type:PARENT</str>
>       </arr>
>       <str name="rows">0</str>
>       <str name="wt">xml</str>
>       <str name="debugQuery">true</str>
>     </lst>
>   </lst>
>   <result name="response" numFound="20108328" start="0"
> maxScore="1.0"></result>
>   <lst name="facets">
>     <long name="count">20108328</long>
>     <lst name="Chart_01_FIELD_NOT_EXISTS">
>       <long name="count">24248</long>
>       <double name="max_score_avg">0.0015258990432200593</double>
>       <double name="avg_score_avg">-2.4744308808973936E-4</double>
>       <double name="min_score_avg">-0.0012372154404486969</double>
>     </lst>
>     <lst name="Chart_01_Bins">
>       <arr name="buckets">
>         <lst>
>           <int name="val">133000008</int>
>           <long name="count">19766128</long>
>           <double name="max_score_avg">1.0301153801720162</double>
>           <double name="avg_score_avg">-0.016091049994686912</double>
>           <double name="min_score_avg">-0.934160420207685</double>
>         </lst>
>         <lst>
>           <int name="val">133000309</int>
>           <long name="count">19678992</long>
>           <double name="max_score_avg">1.027128905235771</double>
>           <double name="avg_score_avg">-0.021377261229524585</double>
>           <double name="min_score_avg">-0.9383299199656859</double>
>         </lst>
>         <lst>
>           <int name="val">133000016</int>
>           <long name="count">19586015</long>
>           <double name="max_score_avg">1.0328805226198583</double>
>           <double name="avg_score_avg">-0.021309381709827595</double>
>           <double name="min_score_avg">-0.9431820282831003</double>
>         </lst>
>         <lst>
>           <int name="val">133000326</int>
>           <long name="count">18991262</long>
>           <double name="max_score_avg">1.0590643252866423</double>
>           <double name="avg_score_avg">-0.019758511191151334</double>
>           <double name="min_score_avg">-0.9636441197805483</double>
>         </lst>
>         <lst>
>           <int name="val">133000019</int>
>           <long name="count">18888512</long>
>           <double name="max_score_avg">1.0563612416377315</double>
>           <double name="avg_score_avg">-0.024104479442487295</double>
>           <double name="min_score_avg">-0.9688924575396817</double>
>         </lst>
>         <lst>
>           <int name="val">133000020</int>
>           <long name="count">18858046</long>
>           <double name="max_score_avg">1.0675188347452709</double>
>           <double name="avg_score_avg">-0.015537465871849449</double>
>           <double name="min_score_avg">-0.9666198510676984</double>
>         </lst>
>         <lst>
>           <int name="val">133000046</int>
>           <long name="count">18854564</long>
>           <double name="max_score_avg">1.0646018922402394</double>
>           <double name="avg_score_avg">-0.01924574809063305</double>
>           <double name="min_score_avg">-0.9673003731236052</double>
>         </lst>
>         <lst>
>           <int name="val">133000173</int>
>           <long name="count">18438355</long>
>           <double name="max_score_avg">1.0699365758185304</double>
>           <double name="avg_score_avg">-0.012621500507322752</double>
>           <double name="min_score_avg">-0.9551372239401853</double>
>         </lst>
>         <lst>
>           <int name="val">133000053</int>
>           <long name="count">18280589</long>
>           <double name="max_score_avg">1.07717860230237</double>
>           <double name="avg_score_avg">-0.02438927275045303</double>
>           <double name="min_score_avg">-0.9861261528306842</double>
>         </lst>
>         <lst>
>           <int name="val">133000416</int>
>           <long name="count">17905999</long>
>           <double name="max_score_avg">1.0807140854212403</double>
>           <double name="avg_score_avg">-0.02857962204396297</double>
>           <double name="min_score_avg">-0.9941415030935342</double>
>         </lst>
>       </arr>
>     </lst>
>   </lst>
>   <lst name="debug">
>     <lst name="track">
>       <str
> name="rid">tas-ds-01.lab.local-0_shard12_replica_n44-1582040461716-15</str>
>       <lst name="EXECUTE_QUERY">
>         <lst name="
> https://tas-ds-02.lab.local:8983/solr/0_shard32_replica_n126/">
>           <str name="QTime">3893</str>
>           <str name="ElapsedTime">3905</str>
>           <str name="RequestPurpose">GET_TOP_IDS,SET_TERM_STATS</str>
>           <str name="NumFound">629250</str>
>           <str
> name="Response">{responseHeader={zkConnected=true,status=0,QTime=3893,params={df=text_en,distrib=false,debug=[false,
> timing, track],_facet_={},fl=[id,
> score],shards.purpose=1064964,hl.fragsize=100000,start=0,fsv=true,fq=[channel:345133,
> content_type:PARENT],shard.url=
> https://tas-ds-02.lab.local:8983/solr/0_shard32_replica_n126/,rows=0,rid=tas-ds-01.lab.local-0_shard12_replica_n44-1582040461716-15,version=2,q=*:*,json.facet={"Chart_01_Bins":{type:terms,
> field:groupIds, mincount:1, limit:10, numBuckets:false, missing:false,
> refine:true ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}},"Chart_01_FIELD_NOT_EXISTS": {type:query, q:
> "-groupIds:[* TO *]" ,facet:{min_score_avg: "avg(min_score)",max_score_avg:
> "avg(max_score)",avg_score_avg:
> "avg(avg_score)"}}},hl.maxAnalyzedChars=100000,omitHeader=false,requestPurpose=GET_TOP_IDS,SET_TERM_STATS,NOW=1582040461715,isShard=true,wt=javabin,debugQuery=false}},response={numFound=629250,start=0,maxScore=1.0,docs=[]},sort_values={},facets={count=629250,Chart_01_Bins={buckets=[{val=133000008,count=618452,min_score_avg=[618452,
> -576939.2808909193],max_score_avg=[618452,
> 637080.180480836],avg_score_avg=[618452, -9495.009733909965]},
> {val=133000309,count=615672,min_score_avg=[615672,
> -576887.1264572814],max_score_avg=[615672,
> 632536.9241082799],avg_score_avg=[615672, -12578.154329540432]},
> {val=133000016,count=612702,min_score_avg=[612702,
> -577158.9922628701],max_score_avg=[612702,
> 633075.5110024717],avg_score_avg=[612702, -12495.717564551383]},
> {val=133000326,count=593872,min_score_avg=[593872,
> -571770.8389462605],max_score_avg=[593872,
> 629157.2776536848],avg_score_avg=[593872, -11311.731255522345]},
> {val=133000019,count=590811,min_score_avg=[590811,
> -571962.5987144224],max_score_avg=[590811,
> 624241.8250667024],avg_score_avg=[590811, -13848.260609685289]},
> {val=133000020,count=589758,min_score_avg=[589758,
> -569468.3429295402],max_score_avg=[589758,
> 629863.7633762769],avg_score_avg=[589758, -8692.508232006314]},
> {val=133000046,count=589574,min_score_avg=[589574,
> -569800.0024026707],max_score_avg=[589574,
> 627875.5197924953],avg_score_avg=[589574, -10939.054679468622]},
> {val=133000173,count=576678,min_score_avg=[576678,
> -550264.2602007724],max_score_avg=[576678,
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         <lst name="
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>         </lst>
>         <lst name="
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>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">627138</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4258</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">628209</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">18</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">628209</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4275</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">627933</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">17</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">627933</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4310</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">628493</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">17</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">628493</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4282</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">628729</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">16</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">628729</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4295</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">629268</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">14</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">629268</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4365</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">628712</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">17</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">628712</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4375</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">627799</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">16</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">627799</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4352</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">628668</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">16</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">628668</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4387</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">628893</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">16</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">628893</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4732</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">629159</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">18</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">629159</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4640</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">629017</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">1649</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">629017</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4734</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">627409</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">1647</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">627409</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetFieldProcessorByHashDV</str>
>           <long name="elapse">4666</long>
>           <str name="field">groupIds</str>
>           <long name="limit">10</long>
>           <long name="domainSize">626614</long>
>           <long name="numBuckets">500</long>
>         </lst>
>         <lst>
>           <str name="processor">FacetQueryProcessor</str>
>           <long name="elapse">1822</long>
>           <arr name="query">
>
> <str>org.apache.lucene.search.BooleanClause:-groupIds:[-2147483648 TO
> 2147483647]</str>
>           </arr>
>           <long name="domainSize">626614</long>
>         </lst>
>       </arr>
>     </lst>
>     <lst name="json">
>       <lst name="facet">
>         <lst name="Chart_01_Bins">
>           <str name="type">terms</str>
>           <str name="field">groupIds</str>
>           <long name="mincount">1</long>
>           <long name="limit">10</long>
>           <bool name="numBuckets">false</bool>
>           <bool name="missing">false</bool>
>           <bool name="refine">true</bool>
>           <lst name="facet">
>             <str name="min_score_avg">avg(min_score)</str>
>             <str name="max_score_avg">avg(max_score)</str>
>             <str name="avg_score_avg">avg(avg_score)</str>
>           </lst>
>         </lst>
>         <lst name="Chart_01_FIELD_NOT_EXISTS">
>           <str name="type">query</str>
>           <str name="q">-groupIds:[* TO *]</str>
>           <lst name="facet">
>             <str name="min_score_avg">avg(min_score)</str>
>             <str name="max_score_avg">avg(max_score)</str>
>             <str name="avg_score_avg">avg(avg_score)</str>
>           </lst>
>         </lst>
>       </lst>
>     </lst>
>     <lst name="timing">
>       <double name="time">146588.0</double>
>       <lst name="prepare">
>         <double name="time">11.0</double>
>         <lst name="query">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="facet">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="facet_module">
>           <double name="time">9.0</double>
>         </lst>
>         <lst name="mlt">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="highlight">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="stats">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="expand">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="terms">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="debug">
>           <double name="time">0.0</double>
>         </lst>
>       </lst>
>       <lst name="process">
>         <double name="time">146537.0</double>
>         <lst name="query">
>           <double name="time">6150.0</double>
>         </lst>
>         <lst name="facet">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="facet_module">
>           <double name="time">140370.0</double>
>         </lst>
>         <lst name="mlt">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="highlight">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="stats">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="expand">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="terms">
>           <double name="time">0.0</double>
>         </lst>
>         <lst name="debug">
>           <double name="time">0.0</double>
>         </lst>
>       </lst>
>     </lst>
>     <str name="rawquerystring">*:*</str>
>     <str name="querystring">*:*</str>
>     <str name="parsedquery">MatchAllDocsQuery(*:*)</str>
>     <str name="parsedquery_toString">*:*</str>
>     <str name="QParser">LuceneQParser</str>
>     <lst name="explain"/></lst>
> </response>
>
>
> Artur Rudenko
> -----Original Message-----
> From: Mikhail Khludnev <[hidden email]>
> Sent: Saturday, February 15, 2020 8:44 PM
> To: solr-user <[hidden email]>
> Subject: Re: Slow quires and facets
>
> I don't have any particular idea. Probably it's worth to start from
> learning debugQuery=true output. There are caveats:
> - it takes a while
> - it's worth to limit shards to a few ones
> - it used to produce incorrect json, and worked in only in wt=xml At least
> it let to sneak something about the longest part of computation.
> Few other thoughts: output with 1K entries doesn't seem like a regular
> search engine response, usually results are scrolled with limit/offset, but
> anyway it looks like analytical job for spark.
>
>
> On Wed, Feb 12, 2020 at 11:32 PM Rudenko, Artur <[hidden email]>
> wrote:
>
> > Hello everyone,
> > I'm am currently investigating a performance issue in our environment:
> > 20M large PARENT documents and 800M nested small CHILD documents.
> > The system inserts about 400K PARENT documents and 16M CHILD documents
> > per day. (Currently we stopped the calls insertion to investigate the
> > performance issue) This is a solr cloud 8.3 environment with 7 servers
> > (64 VCPU 128 GB RAM each, 24GB allocated to Solr) with single
> > collection (32 shards and replication factor 2).
> >
> > We experience generally slow queries (about 4-7 seconds) and facet times.
> > The below query runs in about 14-16 seconds (we have to use limit:-1
> > due to a business case - cardinality is 1K values).
> >
> > fq=channel:345133
> > &fq=content_type:PARENT
> > &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total
> > of int 562 values)
> > &q=*:*
> > &json.facet={
> >                 "Chart_01_Bins":{
> >                                                 type:terms,
> >                                                 field:groupIds,
> >                                                 mincount:1,
> >                                                 limit:-1,
> >                                                 numBuckets:true,
> >                                                 missing:false,
> >                                                 refine:true,
> >                                                 facet:{
> >
> > min_score_avg:"avg(min_score)",
> >
> > max_score_avg:"avg(max_score)",
> >
> > avg_score_avg:"avg(avg_score)"
> >                                                 }
> >                 },
> >                 "Chart_01_FIELD_NOT_EXISTS":{
> >                                 type:query,
> >                                 q:"-groupIds:[* TO *]",
> >                                 facet:{
> >
> > min_score_avg:"avg(min_score)",
> >
> > max_score_avg:"avg(max_score)",
> >
> > avg_score_avg:"avg(avg_score)"
> >                                 }
> >                 }
> > }
> > &rows=0
> >
> > Also, when the facet is simplified, it takes about 4-6 seconds
> >
> > fq=channel:345133
> > &fq=content_type:PARENT
> > &fq=Meta_is_organizationIds:(344996998 344594999 345000001.... total
> > of int 562 values)
> > &q=*:*
> > &json.facet={
> >                 "Chart_01_Bins":{
> >                                 type:terms,
> >                                 field:groupIds,
> >                                 mincount:1,
> >                                 limit:-1,
> >                                 numBuckets:true,
> >                                 missing:false,
> >                                 refine:true
> >                 }
> > }
> > &rows=0
> >
> > Schema relevant fields:
> >
> > <fieldType name="pfloat" class="solr.FloatPointField"
> > docValues="true"/> <fieldType name="pint" class="solr.IntPointField"
> > docValues="true"/>
> >
> > <!-- Currently only 1 value, in the future we expect to have about 25
> > different values --> <field name="channel" type="string"
> > indexed="true" stored="true"
> > required="true" multiValued="false" />
> >
> > <!-- 2 Possible values (PARENT\CHILD) --> <field name="content_type"
> > type="string" indexed="true" stored="true"
> > required="true" multiValued="false" />
> >
> > <!-- Cardinality of 1K values, document may have 0 to all possible
> > values
> > -->
> > <field name="groupIds" type="pint" indexed="true" stored="true"
> > required="false" multiValued="true" />
> >
> > <!-- Float value between -2 to 2, all documents have this field
> > (applied for the below 3 fields) --> <field name="min_score"
> > type="pfloat" indexed="true" stored="true"
> > required="false" multiValued="false" /> <field name="avg_score"
> > type="pfloat" indexed="true" stored="true"
> > required="false" multiValued="false" /> <field name="max_score"
> > type="pfloat" indexed="true" stored="true"
> > required="false" multiValued="false" />
> >
> > <!-- Cardinality with about few thousands values, currently only 1
> > dynamic field exists with this prefix, document may have 1 to all
> > possible values
> > -->
> > <dynamicField name="Meta_is_*" type="pint" indexed="true" stored="true"
> > multiValued="true" />
> >
> >
> > Any suggestions how to proceed with the investigation?
> >
> > Right now we are trying to figure out if using single shard on each
> > machine will help.
> > Artur Rudenko
> > Analytics Developer
> > Customer Engagement Solutions, VERINT
> > T +972.74.747.2536 | M +972.52.425.4686
> >
> >
> >
> > This electronic message may contain proprietary and confidential
> > information of Verint Systems Inc., its affiliates and/or
> > subsidiaries. The information is intended to be for the use of the
> > individual(s) or
> > entity(ies) named above. If you are not the intended recipient (or
> > authorized to receive this e-mail for the intended recipient), you may
> > not use, copy, disclose or distribute to anyone this message or any
> > information contained in this message. If you have received this
> > electronic message in error, please notify us by replying to this e-mail.
> >
>
>
> --
> Sincerely yours
> Mikhail Khludnev
>
>
> This electronic message may contain proprietary and confidential
> information of Verint Systems Inc., its affiliates and/or subsidiaries. The
> information is intended to be for the use of the individual(s) or
> entity(ies) named above. If you are not the intended recipient (or
> authorized to receive this e-mail for the intended recipient), you may not
> use, copy, disclose or distribute to anyone this message or any information
> contained in this message. If you have received this electronic message in
> error, please notify us by replying to this e-mail.
>


--
Sincerely yours
Mikhail Khludnev