"ElasticSearch in action" by Thijs Feryn.
ElasticSearch is a really powerful search engine, NoSQL database & analytics engine. It is fast, it scales and it's a child of the Cloud/BigData generation. This talk will show you how to get things done using ElasticSearch. The focus is on doing actual work, creating actual queries and achieving actual results. Topics that will be covered: - Filters and queries - Cluster, shard and index management - Data mapping - Analyzers and tokenizers - Aggregations - ElasticSearch as part of the ELK stack - Integration in your code.
37. Filter
•Does it match? Yes or no
•When relevance doesn’t matter
•Faster & cacheable
•For non-analyzed data
Query
•How well does it match?
•For full-text search
•On analyzed/tokenized data
38. Match Query
Multi Match Query
Bool Query
Boosting Query
Common Terms Query
Constant Score Query
Dis Max Query
Filtered Query
Fuzzy Like This Query
Fuzzy Like This Field Query
Function Score Query
Fuzzy Query
GeoShape Query
Has Child Query
Has Parent Query
Ids Query
Indices Query
Match All Query
More Like This Query
Nested Query
Prefix Query
Query String Query
Simple Query String Query
Range Query
Regexp Query
Span First Query
Span Multi Term Query
Span Near Query
Span Not Query
Span Or Query
Span Term Query
Term Query
Terms Query
Top Children Query
Wildcard Query
Minimum Should Match
Multi Term Query Rewrite
Template Query
39. And Filter
Bool Filter
Exists Filter
Geo Bounding Box Filter
Geo Distance Filter
Geo Distance Range Filter
Geo Polygon Filter
GeoShape Filter
Geohash Cell Filter
Has Child Filter
Has Parent Filter
Ids Filter
Indices Filter
Limit Filter
Match All Filter
Missing Filter
Nested Filter
Not Filter
Or Filter
Prefix Filter
Query Filter
Range Filter
Regexp Filter
Script Filter
Term Filter
Terms Filter
Type Filter
60. SELECT author, COUNT(guid)
FROM blog.post
GROUP BY author
POST /blog/post/_search?
pretty&search_type=count
{
"aggs": {
"popular_bloggers": {
"terms": {
"field": "author"
}
}
}
}
Only
aggs, no
docs
72. GET /_cat/shards?v
index shard prirep state docs store ip node
my-index 2 r STARTED 6 7.2kb 192.168.10.142 node3
my-index 2 p STARTED 6 9.5kb 192.168.10.142 node2
my-index 0 p STARTED 4 7.1kb 192.168.10.142 node3
my-index 0 r STARTED 4 4.8kb 192.168.10.142 node2
my-index 3 r STARTED 5 7.1kb 192.168.10.142 node1
my-index 3 p STARTED 5 7.2kb 192.168.10.142 node3
my-index 1 p STARTED 1 2.4kb 192.168.10.142 node1
my-index 1 r STARTED 1 2.4kb 192.168.10.142 node2
my-index 4 p STARTED 5 9.5kb 192.168.10.142 node1
my-index 4 r STARTED 5 9.4kb 192.168.10.142 node3
5 shards & a
single replica
by default