ZERO TO HERO ELASTIC

CONFIGURATION ▸ 1. https://github.com/skowron-line/phpers2019-workshop ▸ 2. docker-compose up -d

DOCKER-COMPOSE PS

HTTP://LOCALHOST:9200

HTTP://LOCALHOST:5601

SQL VS ELASTIC Elastic SQL Field Column Document Row Index Table Database Cluster

CREATE INDEX PUT {index}

ADD DOCUMENT POST {index}/_doc

SAMPLE RESPONSE { "_index" : "test", "_type" : "_doc", "_id" : "H9wYAG0Bjhby-D6cxV_8", "_version" : 1, "result" : "created", "_shards" : { "total" : 2, "successful" : 1, "failed" : 0 }, "_seq_no" : 0, "_primary_term" : 1 }

UPDATE DOCUMENT PUT {index}/_doc/{id}

SAMPLE RESPONSE { "_index" : "test", "_type" : "_doc", "_id" : "H9wYAG0Bjhby-D6cxV_8", "_version" : 2, "result" : "updated", "_shards" : { "total" : 2, "successful" : 1, "failed" : 0 }, "_seq_no" : 0, "_primary_term" : 1 }

DELETE DOCUMENT DELETE {index}/_doc

SAMPLE RESPONSE { "_index" : "test", "_type" : "_doc", "_id" : "H9wYAG0Bjhby-D6cxV_8", "_version" : 2, "result" : "deleted", "_shards" : { "total" : 2, "successful" : 1, "failed" : 0 }, "_seq_no" : 0, "_primary_term" : 1 }

While using the _version might seem to work in certain cases, I would recommend to never use it for anything else than optimistic locking of updates. In particular, versions do not carry any meaning: they might look like the number of times a document has been modified but it is not always the case (for instance if you create a new document which has the same ID as a document that you just deleted, the version number of the new document will not be 1), and more importantly it is an implementation detail, this behaviour might change in the future. Versioning

BULK curl -X POST "localhost:9200/_bulk" -H 'Content-Type: application/json' -d' { "create" : { "_index" : "test", "_id" : "1" } } {“field”: “value”, “field”: “value”} { "delete" : { "_index" : "test", "_id" : "1" } } { "update" : {"_id" : "1", "_index" : "test"} } { "doc" : {"field2" : "value2"} }

ANALYSING PROCESS Text -> Char filter -> Tokenizer -> Token filter -> Inverted index

CHAR FILTER The character filter has the ability to perform addition, removal or replacement actions on the input text given to them.

CHAR FILTER “Phpers Summit” “Phpers summit”

TOKENIZER A tokenizer receives a stream of characters, breaks it up into individual tokens (usually individual words), and outputs a stream of tokens

TOKENIZER “Phpers summit najlepsza konferencja w Polsce” “Phpers”, “summit”, “najlepsza”, “konferencja”, “w”, “Polsce”

TOKEN FILTER Token filters can act on the tokens generated from the tokenizers and modify, add or remove them

ANALYZER Analyzer is combination of tokenizer and token filters

BUILD IN ANALYZERS ‣ standard (default) combination of (standard token filter, lowercase and stop token filter) ‣ simple ‣ whitespace ‣ stop ‣ keyword ‣ pattern ‣ language ‣ fingerprint

NORMALIZER Normalizers are similar to analyzers except that they may only emit a single token

INVERTED INDEX Frontend developer w Warszawie PHP Developer Poznań

INVERTED INDEX Token Document 1 Document 2 frontend 1 php 1 developer 1 1 poznan 1 warszawa 1

MAPPING Mapping is the process of defining how a document, and the fields it contains, are stored and indexed. For instance, use mappings to define: ‣ which string fields should be treated as full text fields. ‣ which fields contain numbers, dates, or geolocations. ‣ the format of date values. ‣ custom rules to control the mapping for dynamically added fields.

MAPPING "mappings": { "properties": { "age": { "type": "integer" }, "email": { "type": "keyword" }, "name": { "type": "text" } } }

MAPPING PUT {index} { "mappings": { "properties": { "age": { "type": "integer" }, ... } } }

DYNAMIC MAPPING { "mappings": { "dynamic_date_formats": ["MM/dd/yyyy"] } }

DYNAMIC MAPPING TEMPLATES "dynamic_templates": [ { "strings": { "match_mapping_type": "string", "mapping": { "type": "text", "analyzer": "whitespace" } } } ]

BASIC QUERIES ‣ Match ‣ Multi_match ‣ Term / terms ‣ Range ‣ Wildcard ‣ Query_string ‣ Function_score ‣ Script_score

BOOL QUERIES and, or / must, should

BOOL QUERIES title = "php developer" AND city = "warszawa" { "query": { "must": [ { "term": { "title": { "value": "php developer" } } }, { "term": { "city": { "value": "warszawa" } } } ] } }

LETS GO!