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Renamed words in /docs/canvas/* files according to the quip doc. Elas… #83

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4 changes: 2 additions & 2 deletions docs/canvas/canvas-elements.asciidoc
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Expand Up @@ -21,9 +21,9 @@ By default, most of the elements you create use demo data until you change the d

. To connect the element to your data, select *Data*, then select one of the following data sources:

* *{es} SQL* — Access your data in {es} using SQL syntax. For information about SQL syntax, refer to {ref}/sql-spec.html[SQL language].
* *{opensearch} SQL* — Access your data in {opensearch} using SQL syntax. For information about SQL syntax, refer to {ref}/sql-spec.html[SQL language].

* *{es} documents* &mdash; Access your data in {es} without using aggregations. To use, select an index and fields, and optionally enter a query using the <<lucene-query,Lucene Query Syntax>>. Use the *{es} documents* data source when you have low volume datasets, to view raw documents, or to plot exact, non-aggregated values on a chart.
* *{opensearch} documents* &mdash; Access your data in {opensearch} without using aggregations. To use, select an index and fields, and optionally enter a query using the <<lucene-query,Lucene Query Syntax>>. Use the *{opensearch} documents* data source when you have low volume datasets, to view raw documents, or to plot exact, non-aggregated values on a chart.

* *Timelion* &mdash; Access your time series data using <<timelion,Timelion>> queries. To use Timelion queries, you can enter a query using the <<lucene-query,Lucene Query Syntax>>.

Expand Down
10 changes: 5 additions & 5 deletions docs/canvas/canvas-expression-lifecycle.asciidoc
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Expand Up @@ -40,7 +40,7 @@ filters
| render
----

To produce a filtered set of random data, the expression uses the <<filters_fn, filters>> and <<demodata_fn, demodata>> functions. This time, however, the output becomes the context for the <<pointseries_fn, pointseries>> function, which is a way to aggregate your data, similar to how Elasticsearch works, but more generalized. In this case, the data is split up using the `color` and `size` dimensions, using arguments on the <<pointseries_fn, pointseries>> function. Each unique value in the state column will have an associated size value, which in this case, will be the maximum value of the price column.
To produce a filtered set of random data, the expression uses the <<filters_fn, filters>> and <<demodata_fn, demodata>> functions. This time, however, the output becomes the context for the <<pointseries_fn, pointseries>> function, which is a way to aggregate your data, similar to how OpenSearch works, but more generalized. In this case, the data is split up using the `color` and `size` dimensions, using arguments on the <<pointseries_fn, pointseries>> function. Each unique value in the state column will have an associated size value, which in this case, will be the maximum value of the price column.

If the expression stopped there, it would produce a `pointseries` data type as the output of this expression. But instead of looking at the raw values, the result is inserted into the <<pie_fn, pie>> function, which will produce an output that will render a pie visualization. And just like before, this is inserted into the <<render_fn, render>> function, which is useful for its arguments.

Expand Down Expand Up @@ -211,7 +211,7 @@ demodata

This time, `getCell price` is run, and the result is passed into the next function as the context. Then, each sub-expression of the <<all_fn, all>> function is run, with the context given to their parent, which in this case is the result of `getCell price`. If `all` of these sub-expressions evaluate to `true`, then the `if` condition argument will be true.

Sub-expressions can seem a little foreign, especially if you aren’t a developer, but they’re worth getting familiar with, since they provide a ton of power and flexibility. Since you can nest any expression you want, you can also use this behavior to mix data from multiple indices, or even data from multiple sources. As an example, you could query an API for a value to use as part of the query provided to <<essql_fn, essql>>.
Sub-expressions can seem a little foreign, especially if you aren’t a developer, but they’re worth getting familiar with, since they provide a ton of power and flexibility. Since you can nest any expression you want, you can also use this behavior to mix data from multiple indices, or even data from multiple sources. As an example, you could query an API for a value to use as part of the query provided to <<opensearchsql_fn, opensearchsql>>.

This whole section is really just scratching the surface, but hopefully after reading it, you at least understand how to read expressions and make sense of what they are doing. With a little practice, you’ll get the hang of mixing _context_ and sub-expressions together to turn any input into your desired output.

Expand Down Expand Up @@ -250,12 +250,12 @@ Most `primitive` types can be converted automatically, as you might expect. You

There are other useful type casting options available. For example, something of type `datatable` can be cast to a type `pointseries` simply by only preserving specific columns from the data (namely x, y, size, color, and text). This allows you to treat your source data, which is generally of type `datatable`, like a `pointseries` type simply by convention.

You can fetch data from Elasticsearch using `essql`, which allows you to aggregate the data, provide a custom name for the value, and insert that data directly to another function that only accepts `pointseries` even though `essql` will output a `datatable` type. This makes the following example expression valid:
You can fetch data from OpenSearch using `opensearchsql`, which allows you to aggregate the data, provide a custom name for the value, and insert that data directly to another function that only accepts `pointseries` even though `opensearchsql` will output a `datatable` type. This makes the following example expression valid:

[source,text]
----
essql "SELECT user AS x, sum(cost) AS y FROM index GROUP BY user"
opensearchsql "SELECT user AS x, sum(cost) AS y FROM index GROUP BY user"
| plot
----

In the docs you can see that `essql` returns a `datatable` type, but `plot` expects a `pointseries` context. This works because the `datatable` output will have the columns `x` and `y` as a result of using `AS` in the sql statement to name them. Because the data follows the convention of the `pointseries` data type, casting it into `pointseries` is possible, and it can be passed directly to `plot` as a result.
In the docs you can see that `opensearchsql` returns a `datatable` type, but `plot` expects a `pointseries` context. This works because the `datatable` output will have the columns `x` and `y` as a result of using `AS` in the sql statement to name them. Because the data follows the convention of the `pointseries` data type, casting it into `pointseries` is possible, and it can be passed directly to `plot` as a result.
102 changes: 51 additions & 51 deletions docs/canvas/canvas-function-reference.asciidoc
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Expand Up @@ -134,13 +134,13 @@ any condition={lte 10} condition={gt 30}
filters
| demodata
| filterrows {
getCell "project" | any {eq "elasticsearch"} {eq "kibana"} {eq "x-pack"}
getCell "project" | any {eq "opensearch"} {eq "opensearchDashboards"} {eq "x-pack"}
}
| pointseries color="project" size="max(price)"
| pie
| render
----
This filters out any rows that don’t contain `"elasticsearch"`, `"kibana"` or `"x-pack"` in the `project` field.
This filters out any rows that don’t contain `"opensearch"`, `"opensearchDashboards"` or `"x-pack"` in the `project` field.

*Accepts:* `null`

Expand Down Expand Up @@ -429,7 +429,7 @@ Compares the _context_ to specified value to determine `true` or `false`. Usuall
*Expression syntax*
[source,js]
----
compare "neq" to="elasticsearch"
compare "neq" to="opensearch"
compare op="lte" to=100
----

Expand All @@ -441,15 +441,15 @@ filters
| mapColumn project
fn={getCell project |
switch
{case if={compare eq to=kibana} then=kibana}
{case if={compare eq to=elasticsearch} then=elasticsearch}
{case if={compare eq to=opensearchDashboards} then=opensearchDashboards}
{case if={compare eq to=opensearch} then=opensearch}
default="other"
}
| pointseries size="size(cost)" color="project"
| pie
| render
----
This maps all `project` values that aren’t `"kibana"` and `"elasticsearch"` to `"other"`. Alternatively, you can use the individual comparator functions instead of compare.
This maps all `project` values that aren’t `"opensearchDashboards"` and `"opensearch"` to `"other"`. Alternatively, you can use the individual comparator functions instead of compare.

*Accepts:* `string`, `number`, `boolean`, `null`

Expand Down Expand Up @@ -775,7 +775,7 @@ demodata
| dropdownControl valueColumn=project filterColumn=project
| render
----
This creates a dropdown filter element. It requires a data source and uses the unique values from the given `valueColumn` (i.e. `project`) and applies the filter to the `project` column. Note: `filterColumn` should point to a keyword type field for Elasticsearch data sources.
This creates a dropdown filter element. It requires a data source and uses the unique values from the given `valueColumn` (i.e. `project`) and applies the filter to the `project` column. Note: `filterColumn` should point to a keyword type field for OpenSearch data sources.

*Accepts:* `datatable`

Expand Down Expand Up @@ -825,15 +825,15 @@ filters
| mapColumn project
fn={getCell project |
switch
{case if={eq kibana} then=kibana}
{case if={eq elasticsearch} then=elasticsearch}
{case if={eq opensearchDashboards} then=opensearchDashboards}
{case if={eq opensearch} then=opensearch}
default="other"
}
| pointseries size="size(cost)" color="project"
| pie
| render
----
This changes all values in the project column that don’t equal `"kibana"` or `"elasticsearch"` to `"other"`.
This changes all values in the project column that don’t equal `"opensearchDashboards"` or `"opensearch"` to `"other"`.

*Accepts:* `boolean`, `number`, `string`, `null`

Expand All @@ -852,32 +852,32 @@ Alias: `value`


[float]
[[escount_fn]]
=== `escount`
[[opensearchcount_fn]]
=== `opensearchcount`

Query Elasticsearch for the number of hits matching the specified query.
Query OpenSearch for the number of hits matching the specified query.

*Expression syntax*
[source,js]
----
escount index="logstash-*"
escount "currency:"EUR"" index="kibana_sample_data_ecommerce"
escount query="response:404" index="kibana_sample_data_logs"
opensearchcount index="logstash-*"
opensearchcount "currency:"EUR"" index="opensearch_dashboards_sample_data_ecommerce"
opensearchcount query="response:404" index="opensearch_dashboards_sample_data_logs"
----

*Code example*
[source,text]
----
filters
| escount "Cancelled:true" index="kibana_sample_data_flights"
| opensearchcount "Cancelled:true" index="opensearch_dashboards_sample_data_flights"
| math "value"
| progress shape="semicircle"
label={formatnumber 0,0}
font={font size=24 family="'Open Sans', Helvetica, Arial, sans-serif" color="#000000" align=center}
max={filters | escount index="kibana_sample_data_flights"}
max={filters | opensearchcount index="opensearch_dashboards_sample_data_flights"}
| render
----
The first `escount` expression retrieves the number of flights that were cancelled. The second `escount` expression retrieves the total number of flights.
The first `opensearchcount` expression retrieves the number of flights that were cancelled. The second `opensearchcount` expression retrieves the total number of flights.

*Accepts:* `filter`

Expand All @@ -891,7 +891,7 @@ Aliases: `q`, `query`
|`string`
|A Lucene query string.

Default: `"-_index:.kibana"`
Default: `"-_index:.opensearch-dashboards"`

|`index`
|`string`
Expand All @@ -904,26 +904,26 @@ Default: `"_all"`


[float]
[[esdocs_fn]]
=== `esdocs`
[[opensearchdocs_fn]]
=== `opensearchdocs`

Query Elasticsearch for raw documents. Specify the fields you want to retrieve, especially if you are asking for a lot of rows.
Query OpenSearch for raw documents. Specify the fields you want to retrieve, especially if you are asking for a lot of rows.

*Expression syntax*
[source,js]
----
esdocs index="logstash-*"
esdocs "currency:"EUR"" index="kibana_sample_data_ecommerce"
esdocs query="response:404" index="kibana_sample_data_logs"
esdocs index="kibana_sample_data_flights" count=100
esdocs index="kibana_sample_data_flights" sort="AvgTicketPrice, asc"
opensearchdocs index="logstash-*"
opensearchdocs "currency:"EUR"" index="opensearch_dashboards_sample_data_ecommerce"
opensearchdocs query="response:404" index="opensearch_dashboards_sample_data_logs"
opensearchdocs index="opensearch_dashboards_sample_data_flights" count=100
opensearchdocs index="opensearch_dashboards_sample_data_flights" sort="AvgTicketPrice, asc"
----

*Code example*
[source,text]
----
filters
| esdocs index="kibana_sample_data_ecommerce"
| opensearchdocs index="opensearch_dashboards_sample_data_ecommerce"
fields="customer_gender, taxful_total_price, order_date"
sort="order_date, asc"
count=10000
Expand All @@ -935,7 +935,7 @@ filters
palette={palette "#7ECAE3" "#003A4D" gradient=true}
| render
----
This retrieves the first 10000 documents data from the `kibana_sample_data_ecommerce` index sorted by `order_date` in ascending order, and only requests the `customer_gender`, `taxful_total_price`, and `order_date` fields.
This retrieves the first 10000 documents data from the `opensearch_dashboards_sample_data_ecommerce` index sorted by `order_date` in ascending order, and only requests the `customer_gender`, `taxful_total_price`, and `order_date` fields.

*Accepts:* `filter`

Expand All @@ -949,7 +949,7 @@ Aliases: `q`, `query`
|`string`
|A Lucene query string.

Default: `"-_index:.kibana"`
Default: `"-_index:.opensearch-dashboards"`

|`count`
|`number`
Expand Down Expand Up @@ -980,27 +980,27 @@ Default: `"_all"`


[float]
[[essql_fn]]
=== `essql`
[[opensearchsql_fn]]
=== `opensearchsql`

Queries Elasticsearch using Elasticsearch SQL.
Queries OpenSearch using OpenSearch SQL.

*Expression syntax*
[source,js]
----
essql query="SELECT * FROM "logstash*""
essql "SELECT * FROM "apm*"" count=10000
opensearchsql query="SELECT * FROM "logstash*""
opensearchsql "SELECT * FROM "apm*"" count=10000
----

*Code example*
[source,text]
----
filters
| essql query="SELECT Carrier, FlightDelayMin, AvgTicketPrice FROM "kibana_sample_data_flights""
| opensearchsql query="SELECT Carrier, FlightDelayMin, AvgTicketPrice FROM "opensearch_dashboards_sample_data_flights""
| table
| render
----
This retrieves the `Carrier`, `FlightDelayMin`, and `AvgTicketPrice` fields from the "kibana_sample_data_flights" index.
This retrieves the `Carrier`, `FlightDelayMin`, and `AvgTicketPrice` fields from the "opensearch_dashboards_sample_data_flights" index.

*Accepts:* `filter`

Expand All @@ -1012,7 +1012,7 @@ This retrieves the `Carrier`, `FlightDelayMin`, and `AvgTicketPrice` fields from

Aliases: `q`, `query`
|`string`
|An Elasticsearch SQL query.
|An OpenSearch SQL query.

|`count`
|`number`
Expand Down Expand Up @@ -1050,13 +1050,13 @@ exactly column="project" value="beats"
[source,text]
----
filters
| exactly column=project value=elasticsearch
| exactly column=project value=opensearch
| demodata
| pointseries x=project y="mean(age)"
| plot defaultStyle={seriesStyle bars=1}
| render
----
The `exactly` filter here is added to existing filters retrieved by the `filters` function and further filters down the data to only have `"elasticsearch"` data. The `exactly` filter only applies to this one specific element and will not affect other elements in the workpad.
The `exactly` filter here is added to existing filters retrieved by the `filters` function and further filters down the data to only have `"opensearch"` data. The `exactly` filter only applies to this one specific element and will not affect other elements in the workpad.

*Accepts:* `filter`

Expand Down Expand Up @@ -1096,7 +1096,7 @@ Filters rows in a `datatable` based on the return value of a sub-expression.
*Expression syntax*
[source,js]
----
filterrows {getCell "project" | eq "kibana"}
filterrows {getCell "project" | eq "opensearchDashboards"}
filterrows fn={getCell "age" | gt 50}
----

Expand Down Expand Up @@ -1754,7 +1754,7 @@ Interprets a `TinyMath` math expression using a `number` or `datatable` as _cont

Alias: `expression`
|`string`
|An evaluated `TinyMath` expression. See https://www.elastic.co/guide/en/kibana/current/canvas-tinymath-functions.html.
|An evaluated `TinyMath` expression. See https://www.elastic.co/guide/en/opensearch-dashboards/current/canvas-tinymath-functions.html.
|===

*Returns:* `number`
Expand Down Expand Up @@ -2018,7 +2018,7 @@ Aliases: `exp`, `fn`, `function`
[[pointseries_fn]]
=== `pointseries`

Turn a `datatable` into a point series model. Currently we differentiate measure from dimensions by looking for a `TinyMath` expression. See https://www.elastic.co/guide/en/kibana/current/canvas-tinymath-functions.html. If you enter a `TinyMath` expression in your argument, we treat that argument as a measure, otherwise it is a dimension. Dimensions are combined to create unique keys. Measures are then deduplicated by those keys using the specified `TinyMath` function
Turn a `datatable` into a point series model. Currently we differentiate measure from dimensions by looking for a `TinyMath` expression. See https://www.elastic.co/guide/en/opensearch-dashboards/current/canvas-tinymath-functions.html. If you enter a `TinyMath` expression in your argument, we treat that argument as a measure, otherwise it is a dimension. Dimensions are combined to create unique keys. Measures are then deduplicated by those keys using the specified `TinyMath` function

*Accepts:* `datatable`

Expand Down Expand Up @@ -2702,13 +2702,13 @@ Default: `"@timestamp"`

Aliases: `f`, `start`
|`string`
|The beginning of the range, in ISO8601 or Elasticsearch `datemath` format
|The beginning of the range, in ISO8601 or OpenSearch `datemath` format

|`to`

Aliases: `end`, `t`
|`string`
|The end of the range, in ISO8601 or Elasticsearch `datemath` format
|The end of the range, in ISO8601 or OpenSearch `datemath` format
|===

*Returns:* `filter`
Expand Down Expand Up @@ -2766,11 +2766,11 @@ Aliases: `q`, `query`
|`string`
|A Timelion query

Default: `".es(*)"`
Default: `".opensearch(*)"`

|`from`
|`string`
|The Elasticsearch `datemath` string for the beginning of the time range.
|The OpenSearch `datemath` string for the beginning of the time range.

Default: `"now-1y"`

Expand All @@ -2788,7 +2788,7 @@ Default: `"UTC"`

|`to`
|`string`
|The Elasticsearch `datemath` string for the end of the time range.
|The OpenSearch `datemath` string for the end of the time range.

Default: `"now"`
|===
Expand Down Expand Up @@ -2880,7 +2880,7 @@ Default: `""`
[[var_fn]]
=== `var`

Updates the Kibana global context.
Updates the OpenSearchDashboards global context.

*Accepts:* `any`

Expand All @@ -2902,7 +2902,7 @@ Alias: `name`
[[var_set_fn]]
=== `var_set`

Updates the Kibana global context.
Updates the OpenSearchDashboards global context.

*Accepts:* `any`

Expand Down
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