## Data Profiler

The Data Profiler workflow will be using the `orm-profiler` processor.

After running a Metadata Ingestion workflow, we can run the Data Profiler workflow.
While the `serviceName` will be the same to that was used in Metadata Ingestion, so the ingestion bot can get the `serviceConnection` details from the server.


### 1. Define the YAML Config

This is a sample config for the profiler:

{% codePreview %}

{% codeInfoContainer %}

#### Source Configuration - Source Config

You can find all the definitions and types for the  `sourceConfig` [here](https://github.com/open-metadata/OpenMetadata/blob/main/openmetadata-spec/src/main/resources/json/schema/metadataIngestion/databaseServiceProfilerPipeline.json).

{% codeInfo srNumber=14 %}

**profileSample**: Percentage of data or no. of rows we want to execute the profiler and tests on.

{% /codeInfo %}

{% codeInfo srNumber=15 %}

**threadCount**: Number of threads to use during metric computations.

{% /codeInfo %}

{% codeInfo srNumber=18 %}

**timeoutSeconds**: Profiler Timeout in Seconds

{% /codeInfo %}

{% codeInfo srNumber=19 %}

**databaseFilterPattern**: Regex to only fetch databases that matches the pattern.

{% /codeInfo %}

{% codeInfo srNumber=20 %}

**schemaFilterPattern**: Regex to only fetch tables or databases that matches the pattern.

{% /codeInfo %}

{% codeInfo srNumber=21 %}

**tableFilterPattern**: Regex to only fetch tables or databases that matches the pattern.

{% /codeInfo %}

{% codeInfo srNumber=22 %}

#### Processor Configuration

Choose the `orm-profiler`. Its config can also be updated to define tests from the YAML itself instead of the UI:

**tableConfig**: `tableConfig` allows you to set up some configuration at the table level.
{% /codeInfo %}


{% codeInfo srNumber=23 %}

#### Sink Configuration

To send the metadata to OpenMetadata, it needs to be specified as `type: metadata-rest`.
{% /codeInfo %}


{% partial file="/v1.5/connectors/yaml/workflow-config-def.md" /%}

{% /codeInfoContainer %}

{% codeBlock fileName="filename.yaml" %}


```yaml {% isCodeBlock=true %}
source:
  type: {% $connector %}
  serviceName: {% $connector %}
  sourceConfig:
    config:
      type: Profiler
```
```yaml {% srNumber=14 %}
      # profileSample: 85
```
```yaml {% srNumber=15 %}
      # threadCount: 5
```
```yaml {% srNumber=18 %}
      # timeoutSeconds: 43200
```
```yaml {% srNumber=19 %}
      # databaseFilterPattern:
      #   includes:
      #     - database1
      #     - database2
      #   excludes:
      #     - database3
      #     - database4
```
```yaml {% srNumber=20 %}
      # schemaFilterPattern:
      #   includes:
      #     - schema1
      #     - schema2
      #   excludes:
      #     - schema3
      #     - schema4
```
```yaml {% srNumber=21 %}
      # tableFilterPattern:
      #   includes:
      #     - table1
      #     - table2
      #   excludes:
      #     - table3
      #     - table4
```

```yaml {% srNumber=22 %}
processor:
  type: orm-profiler
  config: {}  # Remove braces if adding properties
    # tableConfig:
    #   - fullyQualifiedName: <table fqn>
    #     profileSample: <number between 0 and 99> # default will be 100 if omitted
    #     profileQuery: <query to use for sampling data for the profiler>
    #     columnConfig:
    #       excludeColumns:
    #         - <column name>
    #       includeColumns:
    #         - columnName: <column name>
    #         - metrics:
    #           - MEAN
    #           - MEDIAN
    #           - ...
    #     partitionConfig:
    #       enablePartitioning: <set to true to use partitioning>
    #       partitionColumnName: <partition column name>
    #       partitionIntervalType: <TIME-UNIT, INTEGER-RANGE, INGESTION-TIME, COLUMN-VALUE>
    #       Pick one of the variation shown below
    #       ----'TIME-UNIT' or 'INGESTION-TIME'-------
    #       partitionInterval: <partition interval>
    #       partitionIntervalUnit: <YEAR, MONTH, DAY, HOUR>
    #       ------------'INTEGER-RANGE'---------------
    #       partitionIntegerRangeStart: <integer>
    #       partitionIntegerRangeEnd: <integer>
    #       -----------'COLUMN-VALUE'----------------
    #       partitionValues:
    #         - <value>
    #         - <value>

```

```yaml {% srNumber=23 %}
sink:
  type: metadata-rest
  config: {}
```

{% partial file="/v1.5/connectors/yaml/workflow-config.md" /%}

{% /codeBlock %}

{% /codePreview %}

- You can learn more about how to configure and run the Profiler Workflow to extract Profiler data and execute the Data Quality from [here](/how-to-guides/data-quality-observability/profiler/workflow)

### 2. Run with the CLI

After saving the YAML config, we will run the command the same way we did for the metadata ingestion:

```bash
metadata profile -c <path-to-yaml>
```

Note now instead of running `ingest`, we are using the `profile` command to select the Profiler workflow.

{% tilesContainer %}

{% tile
title="Data Profiler"
description="Find more information about the Data Profiler here"
link="/how-to-guides/data-quality-observability/profiler/workflow"
/ %}

{% /tilesContainer %}