Elasticsearch - Speed is key

This talk moves beyond the standard introduction to Elasticsearch and focuses on how Elasticsearch tries to fulfill its near real-time contract. Specifically, I’ll show how Elasticsearch manages to be incredibly fast while handling huge amounts of data. After a quick introduction, we will walk through several search features and how the user can get the most out of Elasticsearch.

This talk will go under the hood exploring features like search, aggregations, highlighting, (non-)use of probabilistic data structures and give a quick outlook into future Elasticsearch and Lucene releases.

Presented at CraftConf 2015, http://craft-conf.com"

Transcript

1. Elasticsearch - Speed is key
   Alexander Reelsen
   @spinscale
   

   View Slide

2. www.elastic.co
   2
   • Introduction
   • Elasticsearch
   • Speed by Example
   • Search
   • Aggregations
   • Operating System
   • Distributed aspects
   Agenda
   

   View Slide

3. www.elastic.co
   3
   • Me
   • joined in march 2013
   • working on Elasticsearch
   & Shield
   • Interested in all things
   scale & search
   About
   • Elastic
   • Founded in 2012
   • Behind: Elasticsearch, Logstash,
   Kibana, Marvel, Shield, ES for
   Hadoop, Elasticsearch clients
   • Support subscriptions
   • Public & private trainings
   

   View Slide

4. www.elastic.co
   4
   • Me
   • joined in march 2013
   • working on Elasticsearch
   & Shield
   • Interested in all things
   scale & search
   About
   • Elastic
   • Founded in 2012
   • Behind: Elasticsearch, Logstash,
   Kibana, Marvel, Shield, ES for
   Hadoop, Elasticsearch clients
   • Support subscriptions
   • Public & private trainings
   

   View Slide

5. www.elastic.co
   5
   Elasticsearch - High level overview
   Introduction
   

   View Slide

6. www.elastic.co
   6
   an open source, distributed, scalable,
   highly available, document-oriented, RESTful
   full text search engine
   with real-time search and analytics capabilities
   Elasticsearch is...
   

   View Slide

7. www.elastic.co
   7
   an open source, distributed, scalable, highly available, document-oriented,
   RESTful, full text search engine with real-time search and analytics capabilities
   Elasticsearch is...
   Apache 2.0 License
   https://www.apache.org/licenses/LICENSE-2.0
   

   View Slide

8. www.elastic.co
   8
   an open source, distributed, scalable, highly available, document-oriented,
   RESTful, full text search engine with real-time search and analytics capabilities
   Elasticsearch is...
   

   View Slide

9. www.elastic.co
   9
   an open source, distributed, scalable, highly available, document-oriented,
   RESTful, full text search engine with real-time search and analytics capabilities
   Elasticsearch is...
   

   View Slide

10. www.elastic.co
    10
    an open source, distributed, scalable, highly available, document-oriented,
    RESTful, full text search engine with real-time search and analytics capabilities
    Elasticsearch is...
    

    View Slide

11. www.elastic.co
    11
    an open source, distributed, scalable, highly available, document-oriented,
    RESTful, full text search engine with real-time search and analytics capabilities
    Elasticsearch is...
    {
    "name" : "Craft"
    "geo" : {
    "city" : "Budapest",
    "lat" : 47.49, "lon" : 19.04
    }
    }
    Source:  http://json.org/
    

    View Slide

12. www.elastic.co
    12
    an open source, distributed, scalable, highly available, document-oriented,
    RESTful, full text search engine with real-time search and analytics capabilities
    Elasticsearch is...
    Source:  https://httpwg.github.io/asset/http.svg
    

    View Slide

13. www.elastic.co
    13
    an open source, distributed, scalable, highly available, document-oriented,
    RESTful, full text search engine with real-time search and analytics capabilities
    Elasticsearch is...
    

    View Slide

14. www.elastic.co
    14
    an open source, distributed, scalable, highly available, document-oriented,
    RESTful, full text search engine with real-time search and analytics capabilities
    Elasticsearch is...
    

    View Slide

15. www.elastic.co
    15
    Getting up and running... is easy
    # wget https://download.elastic.co/elasticsearch/
    elasticsearch/elasticsearch-1.5.1.zip
    # unzip elasticsearch-1.5.1.zip
    # cd elasticsearch-1.5.1
    # ./bin/elasticsearch
    # curl http://localhost:9200
    

    View Slide

16. www.elastic.co
    16
    Scaling
    

    View Slide

17. www.elastic.co
    17
    Cluster: A collection of nodes
    node
    cluster
    

    View Slide

18. www.elastic.co
    18
    Cluster: A collection of nodes
    node
    cluster
    node
    

    View Slide

19. www.elastic.co
    cluster
    19
    Cluster: A collection of nodes
    node node
    

    View Slide

20. www.elastic.co
    20
    Cluster: A collection of nodes
    node node node node
    cluster
    

    View Slide

21. www.elastic.co
    21
    Shards: Unit of scale
    a0 a1 a2
    a3
    # curl -X PUT http://localhost:9200/a -d '
    { "index.number_of_shards" : 4 }'
    

    View Slide

22. www.elastic.co
    22
    Shards: Unit of scale
    a0 a1 a2 a3
    # curl -X PUT http://localhost:9200/a -d '
    { "index.number_of_shards" : 4 }'
    

    View Slide

23. www.elastic.co
    23
    Shards: Unit of scale
    a0 a1 a2 a3
    # curl -X PUT http://localhost:9200/a/_settings -d '
    { "index.number_of_replicas" : 1 }'
    

    View Slide

24. www.elastic.co
    24
    Replication
    a0 a1 a2 a3
    # curl -X PUT http://localhost:9200/a/_settings -d '
    { "index.number_of_replicas" : 1 }'
    a0
    a3 a2
    a1
    

    View Slide

25. www.elastic.co
    25
    Search
    

    View Slide

26. www.elastic.co
    26
    CRUD
    PUT books/book/1
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    

    View Slide

27. www.elastic.co
    27
    CRUD
    PUT books/book/1
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    GET books/book/1
    

    View Slide

28. www.elastic.co
    28
    CRUD
    PUT books/book/1
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    GET books/book/1
    DELETE books/book/1
    

    View Slide

29. www.elastic.co
    29
    CRUD
    PUT books/book/1
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    GET books/book/1
    DELETE books/book/1
    GET books/book/_search?q=elasticsearch
    

    View Slide

30. www.elastic.co
    30
    Searching
    GET books/book/_search
    {
    "query" : { "filtered" : {
    "query" : { "match" : { "name" : "elasticsearch" }},
    "filter" : {
    "range" : { "published_at" : { "gte" : "now-1y" } }
    }
    }}
    }
    

    View Slide

31. www.elastic.co
    31
    Searching
    GET books/book/_search
    {
    "query" : { "filtered" : {
    "query" : { "match" : { "name" : "elasticsearch" }},
    "filter" : {
    "range" : { "published_at" : { "gte" : "now-1y" } }
    }
    }}
    }
    {
    "took": 3, "timed_out": false,
    "_shards": { "total": 5, "successful": 5, "failed": 0 },
    "hits": {
    "total": 1, "max_score": 0.15342641,
    "hits": [ {
    "_index": "books", "_type": "book", "_id": "1",
    "_score": 0.15342641,
    "_source": {
    "name": "Elasticsearch - The definitive guide",
    "authors": [ "Clinton Gormley", "Zachary Tong" ],
    "pages": 722, "category": "search"
    "published_at": "2015/01/31",
    } } ] } }
    

    View Slide

32. www.elastic.co
    32
    Searching
    GET books/book/_search
    {
    "query" : { "filtered" : {
    "query" : { "match" : { "name" : "elasticsearch" }},
    "filter" : {
    "range" : { "published_at" : { "gte" : "now-1y" } }
    }
    }},
    "aggs" : {
    "category" : { "terms" : { "field" : "category" } }
    }
    }
    

    View Slide

33. www.elastic.co
    GET books/book/_search
    {
    "query" : { "filtered" : {
    "query" : { "match" : { "name" : "elasticsearch" }},
    "filter" : {
    "range" : { "published_at" : { "gte" : "now-1y" } }
    }
    }},
    "aggs" : {
    "category" : { "terms" : { "field" : "category" } }
    }
    }
    33
    Searching
    {
    "took": 3, "timed_out": false,
    "_shards": { "total": 5, "successful": 5, "failed": 0 },
    "hits": {
    "total": 1, "max_score": 0.15342641,
    "hits": [ ... ]
    },
    "aggregations": {
    "category": {
    "buckets": [
    { "key": "search", "doc_count": 1 },
    { ... }
    ] } } }
    

    View Slide

34. www.elastic.co
    34
    • Hits all relevant shards
    • Searches for top-N results per shard
    • Reduces to top-N total
    • Gets top-N documents/data from relevant shards
    • Returns data to requesting client
    Search
    

    View Slide

35. www.elastic.co
    35
    • Lucene is doing the heavy lifting
    • A single shard is a Lucene index
    • Each field is its own inverted index and can be searched in
    Search on a single shard
    term docid
    clinton 1
    gormley 1
    tong 1
    zachary 1
    

    View Slide

36. www.elastic.co
    36
    • It is very hard to reconstruct the original data from the inverted
    index
    • Solution: Just store the whole document in its own field and
    retrieve it, when returning data to the client
    Example: Return original JSON in search response
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    _source
    

    View Slide

37. www.elastic.co
    Elasticsearch - The definitive guide
    Clinton Gormley Zachary Tong
    722
    2015/01/31
    37
    Example: _all field
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    _all
    

    View Slide

38. www.elastic.co
    Elasticsearch - The definitive guide
    Clinton Gormley Zachary Tong
    38
    Example: copy_to field (name & authors)
    {
    "name" : "Elasticsearch - The definitive guide",
    "authors" : [ "Clinton Gormley", "Zachary Tong" ],
    "pages" : 722,
    "published_at" : "2015/01/31"
    }
    copy_to
    

    View Slide

39. www.elastic.co
    39
    • Filters do not contribute to score & can be cached using a BitSet
    • range filter for a date/price
    • term filter for a category
    • geo filter for a bounding box
    Search: Using filters
    0 1 1 0 0 1 { "term" : { "category" : "search" } }
    0 1 0 0 1 0 { "term" : { "category" : "reduced" } }
    

    View Slide

40. www.elastic.co
    40
    • Problem: How to search in an inverted index for non-existing fields
    (exists & missing filter)?
    • Costly: Need to merge postings lists of all existing terms
    (expensive for high-cardinality fields!)
    • Solution: Index document field names under _field_names
    Filters: Missing fields
    

    View Slide

41. www.elastic.co
    41
    Aggregations
    

    View Slide

42. www.elastic.co
    42
    • Aggregations: Buckets & metrics
    • Aggregations cannot make use of the inverted index
    • Meet Fielddata: Uninverting the index
    • Inverted index: Maps term to document id
    • Fielddata: Maps document id to terms
    Aggregations
    

    View Slide

43. www.elastic.co
    43
    Aggregations
    docid term
    1 Clinton Gormley,
    Zachary Tong
    Inverted Index
    Fielddata
    term docid
    clinton 1
    gormley 1
    tong 1
    zachary 1
    

    View Slide

44. www.elastic.co
    44
    Aggregations
    docid term
    1 Clinton Gormley,
    Zachary Tong
    Inverted Index
    Fielddata
    term docid
    Clinton Gormley 1
    Zachary Tong 1
    

    View Slide

45. www.elastic.co
    45
    • Fielddata is an in-memory data structure, lazily constructed
    • Easy to go OOM (wrong field or too many documents)
    • Solution:
    • circuit breaker
    • doc_values: index-time data structure, no heap, uses the file
    system cache, better compression
    Aggregations: Fielddata
    

    View Slide

46. www.elastic.co
    46
    • Problem: Count distinct elements
    • Naive: Load all data into a set, then check the size (distributed?)
    • Solution: cardinality Aggregation, that uses HyperLogLog++
    • configurable precision, allows to trade memory for accuracy
    • excellent accuracy on low-cardinality sets
    • fixed memory usage: no matter if there are tens or billions of unique values, memory usage only
    depends on configured precision
    Aggregations: Probabilistic data structures
    

    View Slide

47. www.elastic.co
    47
    • Problem: Calculate percentiles
    • Naive: Maintain a sorted list of all values
    • Solution: percentiles Aggregation, that uses T-Digest
    • extreme percentiles are more accurate
    • small sets can be up to 100% accurate
    • while values are added to a bucket, the algorithm trades accuracy for memory savings
    Aggregations: Probabilistic data structures
    

    View Slide

48. www.elastic.co
    48
    Operating system
    & Hardware
    

    View Slide

49. www.elastic.co
    49
    • CPU
    Indexing, searching, highlighting
    • I/O
    Indexing, searching, merging
    • Memory
    Aggregation, indices
    • Network
    Relocation, Snapshot & Restore
    Elasticsearch can easily max out...
    

    View Slide

50. www.elastic.co
    50
    • CPU: Threadpools are sized on number of cores
    • Disk: SSD
    • Memory: ∞
    • Network: GbE or better
    Hardware
    

    View Slide

51. www.elastic.co
    51
    • file system cache
    • file handles
    • memory locking: bootstrap.mlockall
    • dont swap, no OOM killer
    Operating system
    

    View Slide

52. www.elastic.co
    52
    Distributed aspects
    

    View Slide

53. www.elastic.co
    53
    • The network is reliable
    • Latency is zero
    • Bandwidth is infinite
    • The network is secure
    Fallacies of distributed computing
    • Topology doesn't change
    • There is one administrator
    • Transport cost is zero
    • The network is homogeneous
    by  Peter  Deutsch  
    https://en.wikipedia.org/wiki/Fallacies_of_distributed_computing
    

    View Slide

54. www.elastic.co
    54
    Wrapup
    

    View Slide

55. www.elastic.co
    55
    • Speed is key!
    • Search is a tradeoff: Query time vs. index time
    • Benchmark your use-case
    • http://benchmarks.elasticsearch.org/
    Summary
    

    View Slide

56. www.elastic.co
    56
    • Automatic I/O throttling
    • Clusterstate incremental updates
    • Faster recovery
    • Aggregations 2.0
    • Merge queries and filters
    • Reindex API
    • Changes API
    • Expression scripting engine
    Elasticsearch 2.x
    

    View Slide

57. www.elastic.co
    57
    • Speed improvements in queries (must_not, sloppy phrase)
    • Automated caching
    • BitSet compression vastly improved (roaring bitsets)
    • Index compression (on disk + memory)
    • Indexing performance (adaptive merge throttling, SSD detection)
    • Index safety: atomic commits, segment commit identifiers, verify
    integrity at merge
    • ...
    Lucene 5.x
    

    View Slide

58. www.elastic.co
    58
    Alexander Reelsen
    alex@elastic.co
    @spinscale
    Thanks for listening! Questions?
    We’re  hiring  
    https://www.elastic.co/about/careers  
    We’re  helping  
    https://www.elastic.co/subscriptions
    

    View Slide

59. www.elastic.co
    59
    http://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-source-field.html
    http://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-all-field.html
    http://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-field-names-field.html
    http://www.elastic.co/guide/en/elasticsearch/reference/current/mapping-core-types.html#copy-to
    http://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-cardinality-aggregation.html
    http://www.elastic.co/guide/en/elasticsearch/guide/current/cardinality.html
    http://www.elastic.co/guide/en/elasticsearch/guide/current/percentiles.html
    http://www.elastic.co/guide/en/elasticsearch/reference/current/search-aggregations-metrics-percentile-aggregation.html
    http://www.elastic.co/elasticon/2015/sf/elasticsearch-architecture-amusing-algorithms-and-details-on-data-structures/
    http://speakerdeck.com/elastic/all-about-aggregations
    http://www.elastic.co/elasticon/2015/sf/updates-from-lucene-land
    http://speakerdeck.com/elastic/resiliency-in-elasticsearch-and-lucene
    http://www.elastic.co/elasticon/2015/sf/level-up-your-clusters-upgrading-elasticsearch
    http://speakerdeck.com/elasticsearch/maintaining-performance-in-distributed-systems
    References
    

    View Slide