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167 lines
12 KiB
Markdown
167 lines
12 KiB
Markdown
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# Redshift
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For context on getting started with ingestion, check out our [metadata ingestion guide](../README.md).
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## Setup
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To install this plugin, run `pip install 'acryl-datahub[redshift]'`.
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## Capabilities
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This plugin extracts the following:
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- Metadata for databases, schemas, views and tables
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- Column types associated with each table
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- Also supports PostGIS extensions
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- Table, row, and column statistics via optional [SQL profiling](./sql_profiles.md)
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## Quickstart recipe
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Check out the following recipe to get started with ingestion! See [below](#config-details) for full configuration options.
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For general pointers on writing and running a recipe, see our [main recipe guide](../README.md#recipes).
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```yml
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source:
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type: redshift
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config:
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# Coordinates
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host_port: example.something.us-west-2.redshift.amazonaws.com:5439
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database: DemoDatabase
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# Credentials
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username: user
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password: pass
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# Options
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options:
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# driver_option: some-option
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include_views: True # whether to include views, defaults to True
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include_tables: True # whether to include views, defaults to True
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sink:
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# sink configs
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```
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<details>
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<summary>Extra options when running Redshift behind a proxy</summary>
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This requires you to have already installed the Microsoft ODBC Driver for SQL Server.
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See https://docs.microsoft.com/en-us/sql/connect/python/pyodbc/step-1-configure-development-environment-for-pyodbc-python-development?view=sql-server-ver15
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```yml
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source:
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type: redshift
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config:
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host_port: my-proxy-hostname:5439
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options:
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connect_args:
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sslmode: "prefer" # or "require" or "verify-ca"
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sslrootcert: ~ # needed to unpin the AWS Redshift certificate
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sink:
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# sink configs
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```
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</details>
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## Config details
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Note that a `.` is used to denote nested fields in the YAML recipe.
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As a SQL-based service, the Athena integration is also supported by our SQL profiler. See [here](./sql_profiles.md) for more details on configuration.
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| Field | Required | Default | Description |
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| --------------------------- | -------- | -------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `username` | | | Redshift username. |
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| `password` | | | Redshift password. |
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| `host_port` | ✅ | | Redshift host URL. |
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| `database` | | | Redshift database. |
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| `database_alias` | | | Alias to apply to database when ingesting. |
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| `env` | | `"PROD"` | Environment to use in namespace when constructing URNs. |
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| `options.<option>` | | | Any options specified here will be passed to SQLAlchemy's `create_engine` as kwargs.<br />See https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine for details. |
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| `table_pattern.allow` | | | List of regex patterns for tables to include in ingestion. |
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| `table_pattern.deny` | | | List of regex patterns for tables to exclude from ingestion. |
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| `table_pattern.ignoreCase` | | `True` | Whether to ignore case sensitivity during pattern matching. |
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| `schema_pattern.allow` | | | List of regex patterns for schemas to include in ingestion. |
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| `schema_pattern.deny` | | | List of regex patterns for schemas to exclude from ingestion. |
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| `schema_pattern.ignoreCase` | | `True` | Whether to ignore case sensitivity during pattern matching. |
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| `view_pattern.allow` | | | List of regex patterns for views to include in ingestion. |
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| `view_pattern.deny` | | | List of regex patterns for views to exclude from ingestion. |
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| `view_pattern.ignoreCase` | | `True` | Whether to ignore case sensitivity during pattern matching. |
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| `include_tables` | | `True` | Whether tables should be ingested. |
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| `include_views` | | `True` | Whether views should be ingested. |
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## Compatibility
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Coming soon!
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# Redshift-Usage
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This plugin extracts usage statistics for datasets in Amazon Redshift. For context on getting started with ingestion, check out our [metadata ingestion guide](../README.md).
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Note: Usage information is computed by querying the following system tables -
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1. stl_scan
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2. svv_table_info
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3. stl_query
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4. svl_user_info
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##Setup
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To install this plugin, run `pip install 'acryl-datahub[redshift-usage]'`.
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##Capabilities
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This plugin has the below functionalities -
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1. For a specific dataset this plugin ingests the following statistics -
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1. top n queries.
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2. top users.
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3. usage of each column in the dataset.
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2. Aggregation of these statistics into buckets, by day or hour granularity.
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## Sample usage recipe
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Check out the following recipe to get started with ingestion! See [below](#config-details) for full configuration options.
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For general pointers on writing and running a recipe, see our [main recipe guide](../README.md#recipes).
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```yml
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source:
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type: redshift-usage
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config:
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# Coordinates
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host_port: db_host:port
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database: dev
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email_domain: acryl.io
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# Credentials
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username: username
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password: "password"
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sink:
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# sink configs
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```
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### Config details
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Note that a `.` is used to denote nested fields in the YAML recipe.
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By default, we extract usage stats for the last day, with the recommendation that this source is executed every day.
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| Field | Required | Default | Description |
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| --------------------------- | -------- | ---------------------------------------------------------------| --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
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| `username` | | | Redshift username. |
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| `password` | | | Redshift password. |
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| `host_port` | ✅ | | Redshift host URL. |
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| `database` | | | Redshift database. |
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| `env` | | `"PROD"` | Environment to use in namespace when constructing URNs. |
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| `options.<option>` | | | Any options specified here will be passed to SQLAlchemy's `create_engine` as kwargs.<br />See https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine for details. |
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| `email_domain` | ✅ | | Email domain of your organisation so users can be displayed on UI appropriately. |
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| `start_time` | | Last full day in UTC (or hour, depending on `bucket_duration`) | Earliest date of usage to consider. |
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| `end_time` | | Last full day in UTC (or hour, depending on `bucket_duration`) | Latest date of usage to consider. |
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| `top_n_queries` | | `10` | Number of top queries to save to each table. |
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| `bucket_duration` | | `"DAY"` | Size of the time window to aggregate usage stats. |
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## Questions
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If you've got any questions on configuring this source, feel free to ping us on [our Slack](https://slack.datahubproject.io/)!
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