Elastic development. Implementing Big Data search Grzegorz Kołpuć

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Quick look at implementation of search platforms based on ElasticSearch from developer perspective. Full-text search, relevance, geo location, stats, aggregations, alerting - I will show you how pleasant that may be and what traps are waiting for you in the limbo of distributed systems.

Data & Analytics

Grzegorz Kolpuc
@gkolpuc
https://pl.linkedin.com/pub/grzegorz-kolpuc/55/b7/700
grzegorzkolpuc@gmail.com

Financial & Risk IP & Science
Legal News
Tax & Accounting Technology & OPS

1200+
EMPLOYEES IN GDYNIA
150+
IN TECHNOLOGY

Elastic Development
Implementing big data search

Distributed Search Engine
Full-text search
Analytics

open source
document-oriented
based on Lucene
distributed
search
analytics

full-text search
filtering (exact matches, ranges, geo)
cacheable

Plugins
API extensions
scripting
analysis
scripting

Native client
fluent API
single request
bulk requests
bulk processor

standard highlighter
"highlight": {
"StrEvntBriefBlob": [
"continues to see <b>pressure</b> on
internal growth"
]
}
"snippets": [
{
"snippet": "continues to see
<b>pressure</b> on internal growth",
"startOff": 2082,
"endOff": 2126,
"pages": [0],
"snippetID": 1
}
]
fvhEx highlighter

2. Cross cluster search
cluster_threecluster_twocluster_one
newsfilings
research
events

Tribe Node
cluster_threecluster_twocluster_one
newsfilings
research
events
Tribe Node
tribe:
t1:
cluster.name: cluster_one
t2:
cluster.name: cluster_two
t2:
cluster.name: cluster_three

3. Analytics
grouping search result
statistics
metrics

$"aggregations": { "events_grouped": { "terms": {"field": "group"}, "aggregations": { "top_events": { "top_hits": { "size": 10, "sort": [ {"date": {"order": "desc"}} ] } } } } } "aggs": { "level2": { "date_histogram": { "field": "timestamp", "interval": "day", "order": {"_key": "desc"} }, "aggs": { "level3": { "terms": {"field": "host"}, "aggs": { "level4": { "terms": {"field": "apiRequest.appId"} } } }}}}$

$4. Geo search distance filter polygon filter bounding box filter shape query "location": { "type": "geo_shape", "tree": "quadtree", "precision": "1m" } "position": { "type": "geo_point" }$

5. Scripting
if nothing else works
decrease performance

$‘total count of snippets’ { "query": { "function_score": { "query": { "query_string": {"query": "Average "Running five""} }, "script_score": {>>>>}, "boost_mode": "replace" } }, "sort": [{"_score": {}}] } "script_score": { "script_id": "scount6", "lang": "groovy", "params": { "terms": ["average"], "phases": [ { "distance": 1, "phase": ["running","five"] } ], "fields": [{"field": "StrEvntTranscriptBlob", "grp": 111}] } }, "boost_mode": "replace"$

6. Alerting
users subscribed to data
notify users when data changes

Elastic Search
Percolate
Elastic Search
index documentsquery

Low throughput
org.elasticsearch.common.util.concurrent.EsRejectedExecutionException
org.elasticsearch.cluster.block.ClusterBlockException

${ "error": "NoShardAvailableActionException [[std_events_sem_021215][5] null]", “status": 503 }$

Reindex
Apply mapping changes online
Updatable number of shards in the index
Shard splitting

16+
TB of indexed data
7,000,000,000+
documents

100,000+
queries per day (EVENTS)
500,000+
queries per day (expected for research)

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Boston Institute of Analytics

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Elastic development. Implementing Big Data search Grzegorz Kołpuć

2. Grzegorz Kolpuc @gkolpuc https://pl.linkedin.com/pub/grzegorz-kolpuc/55/b7/700 grzegorzkolpuc@gmail.com

3. Event Platform

6. Financial & Risk IP & Science Legal News Tax & Accounting Technology & OPS

8. 60,000+ EMPLOYEES 10,000+ IN TECHNOLOGY

9. 1200+ EMPLOYEES IN GDYNIA 150+ IN TECHNOLOGY

10. Eikon

11.

12. Elastic Development Implementing big data search

13. Distributed Search Engine Full-text search Analytics

14. open source document-oriented based on Lucene distributed search analytics

15. full-text search filtering (exact matches, ranges, geo) cacheable

16. Plugins API extensions scripting analysis scripting

17. Plugins API extensions scripting analysis scripting

18.

19. Marvel

20.

21. Native client fluent API single request bulk requests bulk processor

22. 1. Highlight offset

23. standard highlighter "highlight": { "StrEvntBriefBlob": [ "continues to see <b>pressure</b> on internal growth" ] } "snippets": [ { "snippet": "continues to see <b>pressure</b> on internal growth", "startOff": 2082, "endOff": 2126, "pages": [0], "snippetID": 1 } ] fvhEx highlighter

24. 2. Cross cluster search cluster_threecluster_twocluster_one newsfilings research events

25. Tribe Node cluster_threecluster_twocluster_one newsfilings research events Tribe Node tribe: t1: cluster.name: cluster_one t2: cluster.name: cluster_two t2: cluster.name: cluster_three

26. 3. Analytics grouping search result statistics metrics

27. "aggregations": { "events_grouped": { "terms": {"field": "group"}, "aggregations": { "top_events": { "top_hits": { "size": 10, "sort": [ {"date": {"order": "desc"}} ] } } } } } "aggs": { "level2": { "date_histogram": { "field": "timestamp", "interval": "day", "order": {"_key": "desc"} }, "aggs": { "level3": { "terms": {"field": "host"}, "aggs": { "level4": { "terms": {"field": "apiRequest.appId"} } } }}}}

28. 4. Geo search distance filter polygon filter bounding box filter shape query "location": { "type": "geo_shape", "tree": "quadtree", "precision": "1m" } "position": { "type": "geo_point" }

29. 5. Scripting if nothing else works decrease performance

30. ‘total count of snippets’ { "query": { "function_score": { "query": { "query_string": {"query": "Average "Running five""} }, "script_score": {>>>>}, "boost_mode": "replace" } }, "sort": [{"_score": {}}] } "script_score": { "script_id": "scount6", "lang": "groovy", "params": { "terms": ["average"], "phases": [ { "distance": 1, "phase": ["running","five"] } ], "fields": [{"field": "StrEvntTranscriptBlob", "grp": 111}] } }, "boost_mode": "replace"

31. 6. Alerting users subscribed to data notify users when data changes

32. Elastic Search Percolate Elastic Search index documentsquery

33. Any Cons?

34. Low throughput org.elasticsearch.common.util.concurrent.EsRejectedExecutionException org.elasticsearch.cluster.block.ClusterBlockException

35. { "error": "NoShardAvailableActionException [[std_events_sem_021215][5] null]", “status": 503 }

36. Support

37. Reindex Apply mapping changes online Updatable number of shards in the index Shard splitting

38.

39. 15+ Clusters 3+ percolate clusters

40. ~75 nodes per cluster 250+ indices

41. 16+ TB of indexed data 7,000,000,000+ documents

42. 100,000+ queries per day (EVENTS) 500,000+ queries per day (expected for research)