Delta Lake is a popular open-source storage technology that provides scalable, efficient, and reliable data management for Big Data applications. It provides versioning capabilities that help keep track of changes made to data over time.
In the previous article, we discussed Optimizing Small Files in Delta Lake using OPTIMIZE command. This article will discuss how versioning works in Delta Lake and show code snippets for moving between different versions.
How versioning works in Delta Lake
Delta Lake stores data as a set of parquet files, with each file containing a snapshot of the data at a specific point in time. When modifications are made to the data, Delta Lake creates a new parquet file to store the updated data instead of modifying existing files. This approach allows Delta Lake to create a complete transaction log of all data changes.
Every new version of the data is represented by a new set of parquet files with a metadata file describing the changes made. The metadata file contains information such as the timestamp of the change, the user who made the change, and the type of change made (insert, update, delete).
Delta Lake maintains the transaction log in a directory called the delta log directory. This directory contains all versions of the data and the associated metadata files. It is automatically managed by Delta Lake and should not be modified manually.
Using Spark SQL to move between different versions
Spark SQL is a powerful tool for working with Delta Lake tables. To view the history of a Delta table, you can use the Delta table history command.
SELECT * FROM delta.`/path/to/delta/table/_delta_log`This command shows the complete transaction log for the table, including all changes made to the data. You can filter the results to view specific versions of the data using the “version” column.
To query a Delta table as it existed at a specific point in time, you can use the Delta table time travel feature. This feature allows you to query the table as it existed at a specific version.
SELECT id, name, age FROM delta.`/path/to/delta/table` VERSION AS OF 2This command returns the data from version 2 of the table, with only the “id”, “name”, and “age” columns selected.
It’s essential to note that Delta Lake’s versioning capabilities work automatically, and you do not have to create a new table or manage the transaction log manually.
In summary, Delta Lake is a powerful storage technology that provides versioning capabilities, allowing you to track changes made to data over time. Delta Lake stores data as a series of parquet files, with each file containing a snapshot of the data at a specific point in time. The delta log directory maintains a complete transaction log of all changes made to the data. You can view the transaction log and query a Delta table as it existed at a specific point in time.
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