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Approaching Join Indexyet another one join algorithm
Mikhail Khludnevprincipal engineer
PRIVILEGED AND CONFIDENTIAL
• Grid Dynamics is a Silicon Valley-based leading provider of scalable, next-generation commerce technology solutions
• Record of outperformance with Tier 1 retail clients
• Fortune 1000 client relationships
About Me● principal engineer at Grid Dynamics
● spoke at few last LuceneRevolutions
● contributed BlockJoin query parser for Solr - {!parent}
● blogged about it at http://blog.griddynamics.com/
● tried to fix threads at DataImportHandler
http://google.com/+MikhailKhludnev
You are expected to know● how Lucene searches/filters
● how it counts facets
● that there are segments
● what is DocValues
● why to join
● RDBMS joins: nested loop join, sort-merge join and hash join.
I’m expected to know● query-time join
● index-time join
● yet another one join
Lucene/Solr/Elastic Is Strong
● searching
○ filtering
● analytics
○ facets
○ pivots
○ stats
SKU_ID: 13PROD_ID: 1TYPE: SKU
SIZE: 8COLOR:Blue
SKU_ID: 12PROD_ID: 1TYPE: SKU
SIZE: 8COLOR:Green
There is a weakness
● robust joins
○ multiple entities
○ relations
PROD_ID: 1TYPE: PROD
BRAND: NikeNAME: ShoesPRICE: $50
SKU_ID: 11PROD_ID: 1TYPE: SKU
SIZE: 7COLOR: Black
Joins in General
Joins in General
Joins in General
PK=FK
Joins in General
PK=FK
Joins in General
PK=FK
children
Joins in General
1:M
parents
Executing Join Query
q
Executing Join Query
q
Executing Join Query
q
Executing Join Query
qfq
Executing Join Query
qfq
Join in General
parents ∩ join-relation ∩ children
JoinUtil
q
“25”
“17”
“17”
“25”
“25”“56”
“56”
“56”
“25”
“4”
“61”
FK[doc#]
JoinUtil
q
FK[doc#]
“17”
“17”
“25”
“25”“56”
“56”
“56”
“25”
“4”
“61”
“25”
“25”
“17”
...
JoinUtil
q
PK
“1” →△…“17”→△“25”→△...
“25”
“17”
...
“25”
“17”
“17”
“25”
“25”“56”
“56”
“56”
“25”
“4”
“61”
FK[doc#]
JoinUtil
q
“1” →△…“17”→△“25”→△...
“25”
“17”
...
fq“25”
“17”
“17”
“25”
“25”“56”
“56”
“56”
“25”
“4”
“61”
FK[doc#]PK
Block Joindoc#
Block Joindoc#
432
Block Joindoc#1
0
0
1
0
0
1
0
0
1
0
Block Joindoc#1
0
0
1
0
0
1
0
0
1
0
q
Block Joindoc#1
0
0
1
0
0
1
0
0
1
0
qfq
Block Joindoc#1
0
0
1
0
0
1
0
0
1
0
qfq
Comparison
JoinUtil BlockJoin
searching slow fast
reindexing
Comparison
JoinUtil BlockJoin
searching slow fast
reindexing fast slow
Comparisondoc#
JoinUtil BlockJoin
searching slow fast
reindexing fast slow
Comparisondoc#
JoinUtil BlockJoin
searching slow fast
reindexing fast slow
Comparisondoc#
JoinUtil BlockJoin
searching slow fast
reindexing fast slow
Comparison
JoinUtil BlockJoin
searching slow < ? < fast
reindexing fast > ? > slow
Join Index
q
doc#[doc#]
3
6
0
3
10
0
63
Join Index
q
doc#[doc#]
3
6
0
3
10
0
63
Join Index
q
doc#[doc#]
fq 3
6
0
3
10
0
63
Join Index
qfq
doc#[doc#]
2
4
1
6
5 10
9
8
Join Index
q
doc#[doc#]
fq
2
4
1
6
5 10
9
8
Join Index
q
doc#[doc#]
fq
2
4
1
6
5 10
9
8
meanwhile… in LUCENE-6352
GlobalOrdinalsQuery
“25”
“17”
“17”
“25”
“25”“56”
“56”
“56”
“25”
“4”
“61”
SortedDocValues
GlobalOrdinalsQuery
“25”
“17”
“17”
“25”
“25”“56”
“56”
“56”
“25”
“4”
“61”
SortedDocValues
0 “17”
1 “25”
2 “4”
3 “56”
4 “61”
Ordinals0
0
1
1
3
3
3
1
2
4
1
GlobalOrdinalsQuery
q
0
0
1
1
3
3
3
1
2
4
1
1
1
0
0
0
fq
GlobalOrdinalsQuery
q
0
0
1
1
3
3
3
1
2
4
1
1
1
0
0
0
Benchmarking 2.9 M docs
https://github.com/m-khl/lucene-solr/tree/dvjoin-benchmark-5-1
Latency, ms the bigger the worse
7
28
14
BlockJoin(i-time)
Join Index
JoinUtil(q-time)
GloblOrdinals
●
JoinUtil JoinIndex GlobalOrdinals
BlockJoin
searching slow fast fast fasteranyway
reindexing fast uber slow fast slow
<
doc#[doc#]Indexing is still a problem
2
43
6
103
10
0
63
5 10
9
8
Further Plans 2.0● incremental join-index update
● perhaps just calculate and cache it
● or put to dedicated index
● join in both directions
● calculate optimal execution plan of segments enumeration
● edge case for benchmark
Summary● Joins in General
● JoinUtil vs Block-join vs GlobalOrdinals
● updatable DocValues
● opportunities for improving query-time joins:○ eliminate term enum○ choose lower cardinality side for enumeration○ GlobalOrdinalsJoin
References● Searching relational content with Lucene's BlockJoinQuery
http://blog.mikemccandless.com/● Solr Experience: search parent-child relations. Part I
Solr block-join supporthttp://blog.griddynamics.com/
● https://wiki.apache.org/solr/Join● http://www.slideshare.net/martijnvg/document-relations● SOLR-6234 - {!scorejoin }● LUCENE-6352
● Updatable DocValues Under the Hoodhttp://shaierera.blogspot.com/
● Subject: How to openIfChanged the most recent merge?at: [email protected]
Off scope
Joins’ Zoo in Lucene True Joins
● query-time join
○ JoinUtil
○ {!join }
○ {!scorejoin } - SOLR-6234
● index-time join aka block-join {!
parent}
Joins’ Zoo in Lucene Workarounds
● term positions/SpanQueries
● FieldCollapsing/Grouping
● term decoration
○ spatial
● multivalue fields
True Joins● query-time join
○ JoinUtil
○ {!join },
○ {!scorejoin } - SOLR-6234
● index-time join aka block-join {!
parent}
Joins’ Zoo in Lucene Workarounds
● term positions/SpanQueries
● FieldCollapsing/Grouping
● term decoration
○ spatial
● multivalue fields
True Joins● query-time join
○ JoinUtil
○ {!join },
○ {!scorejoin } - SOLR-6234
● index-time join aka block-join {!
parent}
JoinUtil● query-time
● indexing is fast
● searching is slow, why?
○ expensive term enum
○ single enumeration order
BlockJoin● index-time
● reindexing whole block is as expensive as mandatory
● searching is darn fast, however
○ can’t reorder child docs
store ref = segment#, doc#put ref to previous and current segment in DVwhen add new segment, join IDs with previous segments- for parent, just ref to all children docnums- for children, add plain field refsToSeg:seg#-
when score parents on some segment- buffer them with the link refs, then - intersect buffered link refs with children query on previous segments- search all segments for refsToSeg:seg#, intersect with children query, obtain
perent ref from DV intersect with buffered
