es.md

TL;DR

Elastic search helper. On AWS the first step is to run gen3 es port-forward that forwards a connection to the aws-es-proxy pod, and sets up the ESHOST environment variable, so can curl $ESHOST

Use

gen3 es alias [index-name] [alias-name]

(re)create an alias for the given index if alias-name is given - otherwise just lists the aliases associated with the given index

gen3 es delete index-name[/type/document-id]

delete and index or document

gen3 es dump index-name [size]

dump the contents of an ES index (ex: arranger-projects)

gen3 es export destFolder project-name

gen3 es import srcFolder project-name

gen3 es garbage

list the ES indices that can be garbage collected

• select indices not referenced by an alias ignoring time_ aliases
• select indices that look like an ETL index: NAME_NUMBER
• group the remaining NAME_NUMBER indices by NAME, and remove the largest NUMBER index from each group
• return the remaining indices

gen3 es indices

list the elastic search indices

gen3 es mapping index-name

fetch the type-mapping for the given index

gen3 es port-forward

forward the es-proxy to localhost, and export ESHOST

gen3 es create $indexName mappingFile.json

create a new ES index with the given type mappings

Sample mapping file:

{
    "mappings" : {
      "_doc" : {
        "properties" : {
          "array" : {
            "type" : "keyword"
          },
          "timestamp" : {
            "type" : "date"
          }
        }
      }
    }
}

Also see the jenkins setup scripts in the gen3-qa repo.

gen3 es health

Hit the _cluster/health endpoint.