Minor language tweaks
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@ -24,25 +24,26 @@ Your use cases will help you decide which method to use to create transform jobs
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## Create a transform job
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If you don't have any data in your cluster, you can add the sample data within OpenSearch Dashboards to try out transform jobs. Otherwise, after launching OpenSearch Dashboards, choose **Index Management**. Select **Transform Jobs**, and choose **Create Transform Job**.
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If you don't have any data in your cluster, you can use the sample data within OpenSearch Dashboards to try out transform jobs. Otherwise, after launching OpenSearch Dashboards, choose **Index Management**. Select **Transform Jobs**, and choose **Create Transform Job**.
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### Step 1: Choose indices
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1. In the **Job name and description** section, specify a name and an optional description for your job.
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2. In the **Indices** section, select the source and target index. You can either select an existing target index or create a new one by entering a name for your new index. If you want to transform just a subset of your source index, choose **Add Data Filter** and use the OpenSearch query DSL to specify a subset of your source index. For more information about the OpenSearch query DSL, see [query DSL](../../opensearch/query-dsl/).
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2. In the **Indices** section, select the source and target index. You can either select an existing target index or create a new one by entering a name for your new index. If you want to transform just a subset of your source index, choose **Add Data Filter**, and use the OpenSearch query DSL to specify a subset of your source index. For more information about the OpenSearch query DSL, see [query DSL](../../opensearch/query-dsl/).
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3. Choose **Next**.
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### Step 2: Select fields to transform
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After specifying the indices, you can select the fields you want to transform, as well as whether to transform them using groupings or aggregations.
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After specifying the indices, you can select the fields you want to use in your transform job, as well as whether to use groupings or aggregations.
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You can use groupings to place your data into separate buckets in your transformed index. For example, if you want to see how many people logged in to a system separated into days of the week, you can group the `day_of_week` field into a target field of `day`, and your transformed index will sort your data into separate groups.
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On the other hand, aggregations let you perform simple calculations. For example, you can include an aggregation in your transform job to define a new field of `sum_of_total_ticket_price` that calculates the sum of all airplane tickets, and then analyze the newly summer data within your transformed index.
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1. In the data table, select the fields you want to transform and expand the drop-down menu to choose the grouping or aggregation you want to use.
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1. In the data table, select the fields you want to transform and expand the drop-down menu within the column header to choose the grouping or aggregation you want to use.
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Currently, transform jobs support histogram, date_histogram, and terms groupings. For more information about groupings, see [Bucket Aggregations](../../opensearch/bucket-agg/). In terms of aggregations, you can select from `sum`, `avg`, `max`, `min`, `value_count`, `percentiles`, and `scripted_metric`. For more information about aggregations, see [Metric Aggregations](../../opensearch/metric-agg/).
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2. Repeat step 1 for any other fields that you want to transform.
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3. After selecting the fields that you want to transform and verifying the transformation, choose **Next**.
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@ -60,7 +61,7 @@ After confirming your transform job’s details are correct, choose **Create Tra
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### Step 5: Search through the transformed index.
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Once the transform job finishes, you can use the _search API operation to search the target index.
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Once the transform job finishes, you can use the `_search` API operation to search the target index.
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```json
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GET target_index/_search
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@ -135,9 +135,9 @@ source_index | String | The source index whose data to transform. | Yes
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target_index | String | The target index the newly transformed data is added into. You can create a new index or update an existing one. | Yes
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data_selection_query | JSON | The query DSL to use to filter a subset of the source index for the transform job. See [query DSL](../../../opensearch/query-dsl) for more information. | Yes
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page_size | Integer | The number of fields to transform at a time. Higher number means higher performance but requires more memory and can cause higher latency. (Default: 1) | Yes
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groups | Array | Specifies the grouping(s) to use in the transform job. Supported groups are `terms`, `histogram`, and `date_histogram`. For more information, see [Bucket Aggregations](../../../opensearch/bucket-agg). | Yes
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groups | Array | Specifies the grouping(s) to use in the transform job. Supported groups are `terms`, `histogram`, and `date_histogram`. For more information, see [Bucket Aggregations](../../../opensearch/bucket-agg). | Yes if not using aggregations
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source_field | String | The field(s) to transform | Yes
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aggregations | JSON | The aggregations to use in the transform job. Supported aggregations are: `sum`, `max`, `min`, `value_count`, `avg`, `scripted_metric`, and `percentiles`. For more information, see [Metric Aggregations](../../../opensearch/metric-agg). | No
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aggregations | JSON | The aggregations to use in the transform job. Supported aggregations are: `sum`, `max`, `min`, `value_count`, `avg`, `scripted_metric`, and `percentiles`. For more information, see [Metric Aggregations](../../../opensearch/metric-agg). | Yes if not using groups
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## Update a transform job
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