This section provides a high-level overview of the setup and load workflow for external tables that reference Amazon S3 stages. Metadata of specified objects and the credits billed for these operations. Users with the ACCOUNTADMIN role, or a role with the global MONITOR USAGE privilege, can query theĪUTO_REFRESH_REGISTRATION_HISTORY table function to retrieve the history of data files registered in the Refreshes of external tables enhanced with Delta Lake rely on user-managed compute resources (i.e. Manual refreshes of standard external tables are cloud services operations only however, manual This overhead is charged in accordance with the standard cloud services billing model, In addition, a small maintenance overhead is charged for manually refreshing the external table metadata (using ALTER EXTERNAL TABLE … You can estimate this charge by querying the PIPE_USAGE_HISTORY function or examining the Account Usage PIPE_USAGE_HISTORY View. This overheadĬharge appears as Snowpipe charges in your billing statement because Snowpipe is used for event notifications for the automatic external Relation to the number of files added in cloud storage for the external stages and paths specified for your external tables. Instead, periodically execute anĪLTER EXTERNAL TABLE … REFRESH statement to register any added or removed files.įor more information, including examples, see CREATE EXTERNAL TABLE.Īn overhead to manage event notifications for the automatic refreshing of external table metadata is included in your charges. Therefore, the ability toĪutomatically refresh the metadata is not available for external tables that reference Delta Lake files. Note that the ordering of event notifications triggered by DDL operations in cloud storage is not guaranteed. In the background, the refresh performs add and remove file operations to keep the external table metadata in sync. When the metadata for an external table is refreshed, Snowflake parses the Delta Lake transaction logs and determines which Parquet filesĪre current. When this parameter is set, the external table scans for Delta Lake transaction log files in the LOCATION location. To create an external table that references a Delta Lake, set the TABLE_FORMAT = DELTA parameter in the CREATE EXTERNAL TABLE Create external tables that reference yourĬloud storage locations enhanced with Delta Lake. All data in Delta Lake is stored in Apache Parquet format. For examples, seeĭelta Lake is a table format on your data lake that supports ACID (atomicity, consistency, isolation, durability) The following sections explain the different options for adding partitions in greater detail. Table is created, the method by which partitions are added cannot be changed. Partition columns are defined when an external table is created, using the CREATE EXTERNAL TABLE … PARTITION BY syntax. Response time is faster when processing a small part of the data instead of scanning the entire data set.īased on your individual use cases, you can either:Īdd new partitions automatically by refreshing an external table that defines an expression for each partition column. Because the external data is partitioned into separate slices/parts, query Partitions are stored in the external table metadata.īenefits of partitioning include improved query performance. Partitioning divides your external table data into multiple parts usingĪn external table definition can include multiple partition columns, which impose a multi-dimensional structure on the external data. Include date, time, country, or similar dimensions in the path. We strongly recommend partitioning your external tables, which requires that your underlying data is organized using logical paths that
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