What I have been doing is evaluating Elasticsearch. The indexing, searching (Phrase, Similarity, Structured, Full Text, Complex), clustering etc. In this blog I will just try and simplify the learning curve.<\/p>\n\n\n\n
https:\/\/myserver.elastic.com:9200\/_cat\/health?v<\/a><\/p>Returns information about your cluster<\/cite><\/blockquote>\n\n\n\n
epoch 1582199918 \ntimestamp 11:58:38\ncluster samarthya-cluster\nstatus yellow\nnode.total 4\nnode.data 4\nshards 108\npri 64\nrelo 0\ninit 0\nunassign 17\npending_tasks 0\nmax_task_wait_time -\nactive_shards_percent. 86.4%<\/pre>\n\n\n\nAction Time<\/h2>\n\n\n\n
- Let’s add a document into an index.<\/li><\/ol>\n\n\n\n
\nThe most powerful aspect of elasticsearch is Dynamic Mapping<\/a> (more details below) which allows you to explore your data as quickly as possible. <\/p>\n\n\n\n
To index a document, you don\u2019t have to first create an index, define a mapping type, and define your fields\u2009\u2014\u2009you can just index a document and the index, type, and fields will spring to life automatically<\/p>\n\n\n\n
In the command below I am trying to issue a request for a document with
_id<\/code> 1.<\/p>\n\n\n\n1. GET \/profile\/_doc\/1<\/h4>\n\n\n\n
A sample request for an index
profile<\/code> which does not exists at the moment.<\/p>\n\n\n\n{\n \"error\" : {\n \"root_cause\" : [\n {\n \"type\" : \"index_not_found_exception\",\n \"reason\" : \"no such index [profile]\",\n \"resource.type\" : \"index_expression\",\n \"resource.id\" : \"profile\",\n \"index_uuid\" : \"na<\/em>\",\n \"index\" : \"profile\"\n }\n ],\n \"type\" : \"index_not_found_exception\",\n \"reason\" : \"no such index [profile]\",\n \"resource.type\" : \"index_expression\",\n \"resource.id\" : \"profile\",\n \"index_uuid\" : \"na<\/em>\",\n \"index\" : \"profile\"\n },\n \"status\" : 404\n }\n<\/pre>\n<\/div><\/div>\n\n\n\nOne way to create a non existing index is by using
PUT<\/code>. Dynamically the mapping will be put in place and you can execute theGET<\/code> above to see the details.<\/p>\n\n\n\n2. PUT \/profile\/_doc\/1<\/h4>\n\n\n\n
\n{\n \"name\": \"Saurabh Sharma\",\n \"age\": \"60\",\n \"title\": \"Mr.\",\n \"role\": \"Tech lead\",\n \"org\": \"Security\"\n }<\/pre>\n<\/div><\/div>\n\n\n\n\nIn case of successful execution you should see an output like under<\/p>\n\n\n\n
{\n \"_index\" : \"profile\",\n \"_type\" : \"_doc\",\n \"_id\" : \"1\",\n \"_version\" : 1,\n \"result\" : \"created\",<\/strong>\n \"_shards\" : {\n \"total\" : 2,<\/strong>\n \"successful\" : 1,\n \"failed\" : 0\n },\n \"_seq_no\" : 0,\n \"_primary_term\" : 1\n }<\/pre>\n<\/div><\/div>\n\n\n\nThe document that was passed as JSON body is now successfully indexed.<\/p>\n\n\n\n
The automatic detection and addition of new fields is called dynamic mapping<\/em>.<\/p>Dynamic Mapping<\/cite><\/blockquote>\n\n\n\n
If no body is provided it might throw an error like below.<\/h4>\n\n\n\n
\n{\n \"error\": {\n \"root_cause\": [\n {\n \"type\": \"parse_exception\",\n \"reason\": \"request body is required\"\n }\n ],\n \"type\": \"parse_exception\",\n \"reason\": \"request body is required\"\n },\n \"status\": 400\n }<\/pre>\n<\/div><\/div>\n\n\n\nIf the GET is issued again. It will return the document indexed. You can look at the fields that have an
_<\/code> at the start like_type<\/code>,id<\/code>,version<\/code> etc. These are called metafields<\/a>.<\/p>\n\n\n\nGET \/profile\/_doc\/1<\/h4>\n\n\n\n
\n{\n \"_index\" : \"profile\",\n \"_type\" : \"_doc\",\n \"_id\" : \"1\",\n \"_version\" : 1,\n \"_seq_no\" : 0,\n \"_primary_term\" : 1,\n \"found\" : true,\n \"_source\" : {\n \"name\" : \"Saurabh Sharma\",\n \"age\" : \"60\",\n \"title\" : \"Mr.\",\n \"role\" : \"Tech lead\",\n \"org\" : \"Security\"\n }\n }<\/pre>\n<\/div><\/div>\n\n\n\nOne can use the BULK API<\/a>, to ingest more than one document.<\/p>\n\n\n\n
Search<\/h2>\n\n\n\n
GET \/profile\/_search<\/h4>\n\n\n\n
\n{\n \"query\": { \"match_all\": {}},\n \"sort\": [\n {\n \"age\": \"asc\"\n }\n ]\n }<\/pre>\n<\/div><\/div>\n\n\n\nWe hare looking for all the matches and sorting it by age in ascending order.<\/p>\n\n\n\n
Result : Exception<\/h4>\n\n\n\n
{\n \"error\": {\n \"root_cause\": [\n {\n \"type\": \"illegal_argument_exception\",\n \"reason\": \"Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead.\"\n }\n ],\n \"type\": \"search_phase_execution_exception\",\n \"reason\": \"all shards failed\",\n \"phase\": \"query\",\n \"grouped\": true,\n \"failed_shards\": [\n {\n \"shard\": 0,\n \"index\": \"profile\",\n \"node\": \"mrTQQhMPQfWPF6q_IGfs5Q\",\n \"reason\": {\n \"type\": \"illegal_argument_exception\",\n \"reason\": \"Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead.\"\n }\n }\n ],\n \"caused_by\": {\n \"type\": \"illegal_argument_exception\",\n \"reason\": \"Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead.\",\n \"caused_by\": {\n \"type\": \"illegal_argument_exception\",\n \"reason\": \"Fielddata is disabled on text fields by default. Set fielddata=true on [age] in order to load fielddata in memory by uninverting the inverted index. Note that this can however use significant memory. Alternatively use a keyword field instead.\"\n }\n }\n },\n \"status\": 400\n }<\/pre>\n\n\n\n