OpenSearch/docs/painless/painless-contexts/painless-context-examples.a...

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[[painless-context-examples]]
=== Context examples
To run the examples, index the sample seat data into Elasticsearch. The examples
must be run sequentially to work correctly.
. Download the
https://download.elastic.co/demos/painless/contexts/seats.json[seat data]. This
data set contains booking information for a collection of plays. Each document
represents a single seat for a play at a particular theater on a specific date
and time.
+
Each document contains the following fields:
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`theatre` ({ref}/keyword.html[`keyword`])::
The name of the theater the play is in.
`play` ({ref}/text.html[`text`])::
The name of the play.
`actors` ({ref}/text.html[`text`])::
A list of actors in the play.
`row` ({ref}/number.html[`integer`])::
The row of the seat.
`number` ({ref}/number.html[`integer`])::
The number of the seat within a row.
`cost` ({ref}/number.html[`double`])::
The cost of the ticket for the seat.
`sold` ({ref}/boolean.html[`boolean`])::
Whether or not the seat is sold.
`datetime` ({ref}/date.html[`date`])::
The date and time of the play as a date object.
`date` ({ref}/keyword.html[`keyword`])::
The date of the play as a keyword.
`time` ({ref}/keyword.html[`keyword`])::
The time of the play as a keyword.
. {defguide}/running-elasticsearch.html[Start] Elasticsearch. Note these
examples assume Elasticsearch and Kibana are running locally. To use the Console
editor with a remote Kibana instance, click the settings icon and enter the
Console URL. To submit a cURL request to a remote Elasticsearch instance, edit
the request URL.
. Create {ref}/mapping.html[mappings] for the sample data:
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[source,js]
----
PUT /seats
{
"mappings": {
"_doc": {
"properties": {
"theatre": { "type": "keyword" },
"play": { "type": "text" },
"actors": { "type": "text" },
"row": { "type": "integer" },
"number": { "type": "integer" },
"cost": { "type": "double" },
"sold": { "type": "boolean" },
"datetime": { "type": "date" },
"date": { "type": "keyword" },
"time": { "type": "keyword" }
}
}
}
}
----
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// CONSOLE
. Run the <<painless-ingest-processor-context, ingest processor context>>
example. This sets up a script ingest processor used on each document as the
seat data is indexed.
. Index the seat data:
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[source,js]
----
curl -XPOST localhost:9200/seats/seat/_bulk?pipeline=seats -H "Content-Type: application/x-ndjson" --data-binary "@/<local-file-path>/seats.json"
----
// NOTCONSOLE