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AWS Documentation » AWS Glue » Developer Guide » Populating the AWS Glue Data Catalog » Defining Crawlers » Configuring a Crawler
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Configuring a Crawler

When a crawler runs, it might encounter changes to your data store that result in a schema or partition that is different from a previous crawl. You can use the AWS Management Console or the AWS Glue API to configure how your crawler processes certain types of changes.

Configuring a Crawler on the AWS Glue Console

When you define a crawler using the AWS Glue console, you have several options for configuring the behavior of your crawler. For more information about using the AWS Glue console to add a crawler, see Working with Crawlers on the AWS Glue Console.

When a crawler runs against a previously crawled data store, it might discover that a schema has changed or that some objects in the data store have been deleted. The crawler logs changes to a schema. Depending on the source type for the crawler, new tables and partitions might be created regardless of the schema change policy.

To specify what the crawler does when it finds changes in the schema, you can choose one of the following actions on the console:

  • Update the table definition in the Data Catalog – Add new columns, remove missing columns, and modify the definitions of existing columns in the AWS Glue Data Catalog. Remove any metadata that is not set by the crawler. This is the default setting.

  • Add new columns only – For tables that map to an Amazon S3 data store, add new columns as they are discovered, but don't remove or change the type of existing columns in the Data Catalog. Choose this option when the current columns in the Data Catalog are correct and you don't want the crawler to remove or change the type of the existing columns. If a fundamental Amazon S3 table attribute changes, such as classification, compression type, or CSV delimiter, mark the table as deprecated. Maintain input format and output format as they exist in the Data Catalog. Update SerDe parameters only if the parameter is one that is set by the crawler. For all other data stores, modify existing column definitions.

  • Ignore the change and don't update the table in the Data Catalog – Only new tables and partitions are created.

A crawler might also discover new or changed partitions. By default, new partitions are added and existing partitions are updated if they have changed. In addition, you can set a crawler configuration option to Update all new and existing partitions with metadata from the table on the AWS Glue console. When this option is set, partitions inherit metadata properties—such as their classification, input format, output format, SerDe information, and schema—from their parent table. Any changes to these properties in a table are propagated to its partitions. When this configuration option is set on an existing crawler, existing partitions are updated to match the properties of their parent table the next time the crawler runs.

To specify what the crawler does when it finds a deleted object in the data store, choose one of the following actions:

  • Delete tables and partitions from the Data Catalog

  • Ignore the change and don't update the table in the Data Catalog

  • Mark the table as deprecated in the Data Catalog – This is the default setting.

Configuring a Crawler Using the API

When you define a crawler using the AWS Glue API, you can choose from several fields to configure your crawler. The SchemaChangePolicy in the crawler API determines what the crawler does when it discovers a changed schema or a deleted object. The crawler logs schema changes as it runs.

When a crawler runs, new tables and partitions are always created regardless of the schema change policy. You can choose one of the following actions in the UpdateBehavior field in the SchemaChangePolicy structure to determine what the crawler does when it finds a changed table schema:

  • UPDATE_IN_DATABASE – Update the table in the AWS Glue Data Catalog. Add new columns, remove missing columns, and modify the definitions of existing columns. Remove any metadata that is not set by the crawler.

  • LOG – Ignore the changes, and don't update the table in the Data Catalog.

You can also override the SchemaChangePolicy structure using a JSON object supplied in the crawler API Configuration field. This JSON object can contain a key-value pair to set the policy to not update existing columns and only add new columns. For example, provide the following JSON object as a string: 

{
   "Version": 1.0,
   "CrawlerOutput": {
      "Tables": { "AddOrUpdateBehavior": "MergeNewColumns" }
   }
}

This option corresponds to the Add new columns only option on the AWS Glue console. It overrides the SchemaChangePolicy structure for tables that result from crawling Amazon S3 data stores only. Choose this option if you want to maintain the metadata as it exists in the Data Catalog (the source of truth). New columns are added as they are encountered, including nested data types. But existing columns are not removed, and their type is not changed. If an Amazon S3 table attribute changes significantly, mark the table as deprecated, and log a warning that an incompatible attribute needs to be resolved.

When a crawler runs against a previously crawled data store, it might discover new or changed partitions. By default, new partitions are added and existing partitions are updated if they have changed. In addition, you can set a crawler configuration option to InheritFromTable (corresponding to the Update all new and existing partitions with metadata from the table option on the AWS Glue console). When this option is set, partitions inherit metadata properties from their parent table, such as their classification, input format, output format, SerDe information, and schema. Any property changes to the parent table are propagated to its partitions.

When this configuration option is set on an existing crawler, existing partitions are updated to match the properties of their parent table the next time the crawler runs. This behavior is set crawler API Configuration field. For example, provide the following JSON object as a string: 

{
   "Version": 1.0,
   "CrawlerOutput": {
      "Partitions": { "AddOrUpdateBehavior": "InheritFromTable" }
   }
}

The crawler API Configuration field can set multiple configuration options. For example, to configure the crawler output for both partitions and tables, you can provide a string representation of the following JSON object: 

{
    "Version": 1.0,
    "CrawlerOutput": {
       "Partitions": { "AddOrUpdateBehavior": "InheritFromTable" },
       "Tables": {"AddOrUpdateBehavior": "MergeNewColumns" }
    }
}

You can choose one of the following actions to determine what the crawler does when it finds a deleted object in the data store. The DeleteBehavior field in the SchemaChangePolicy structure in the crawler API sets the behavior of the crawler when it discovers a deleted object.

  • DELETE_FROM_DATABASE – Delete tables and partitions from the Data Catalog.

  • LOG – Ignore the change. Don't update the Data Catalog. Write a log message instead.

  • DEPRECATE_IN_DATABASE – Mark the table as deprecated in the Data Catalog. This is the default setting.

How to Prevent the Crawler from Changing an Existing Schema

If you don't want a crawler to overwrite updates you made to existing fields in an Amazon S3 table definition, choose the option on the console to Add new columns only or set the configuration option MergeNewColumns. This applies to tables and partitions, unless Partitions.AddOrUpdateBehavior is overridden to InheritFromTable.

If you don't want a table schema to change at all when a crawler runs, set the schema change policy to LOG. You can also set a configuration option that sets partition schemas to inherit from the table.

If you are configuring the crawler on the console, you can choose the following actions:

  • Ignore the change and don't update the table in the Data Catalog

  • Update all new and existing partitions with metadata from the table

When you configure the crawler using the API, set the following parameters:

  • Set the UpdateBehavior field in SchemaChangePolicy structure to LOG.

  • Set the Configuration field with a string representation of the following JSON object in the crawler API; for example: 

    {
   "Version": 1.0,
   "CrawlerOutput": {
      "Partitions": { "AddOrUpdateBehavior": "InheritFromTable" }
   }
}

How to Create a Single Schema for Each Amazon S3 Include Path

By default, when a crawler defines tables for data stored in Amazon S3, it considers both data compatibility and schema similarity. Data compatibility factors that it considers include whether the data is of the same format (for example, JSON), the same compression type (for example, GZIP), the structure of the Amazon S3 path, and other data attributes. Schema similarity is a measure of how closely the schemas of separate Amazon S3 objects are similar.

You can configure a crawler to CombineCompatibleSchemas into a common table definition when possible. With this option, the crawler still considers data compatibility, but ignores the similarity of the specific schemas when evaluating Amazon S3 objects in the specified include path.

If you are configuring the crawler on the console, to combine schemas, select the crawler option Create a single schema for each S3 path.

When you configure the crawler using the API, set the following configuration option:

  • Set the Configuration field with a string representation of the following JSON object in the crawler API; for example: 

    {
   "Version": 1.0,
   "Grouping": {
      "TableGroupingPolicy": "CombineCompatibleSchemas" }
}

To help illustrate this option, suppose that you define a crawler with an include path s3://bucket/table1/. When the crawler runs, it finds two JSON files with the following characteristics:

  • File 1 – S3://bucket/table1/year=2017/data1.json

  • File content – {“A”: 1, “B”: 2}

  • Schema – A:int, B:int

  • File 2 – S3://bucket/table1/year=2018/data2.json

  • File content – {“C”: 3, “D”: 4}

  • Schema – C: int, D: int

By default, the crawler creates two tables, named year_2017 and year_2018 because the schemas are not sufficiently similar. However, if the option Create a single schema for each S3 path is selected, and if the data is compatible, the crawler creates one table. The table has the schema A:int,B:int,C:int,D:int and partitionKey year:string.