Apache Iceberg 101 Course: How to Maintain Iceberg Tables (#11)

This Apache Iceberg 101 Course (#11) provides a comprehensive overview of how to maintain Iceberg tables. This course will discuss topics such as compaction with rewriteDataFiles, expiring snapshots, managing metadata files, and cleaning up orphan files.

Apache Iceberg is an open source data lakehouse table format that provides a unified data set structure for both batch and streaming workloads. It helps simplify the process of managing large-scale data lakes on distributed storage systems by providing a unified format for storing data. Apache Iceberg is designed to support the evolution of schema and evolution of query semantics across different types of workloads.

Compaction with rewriteDataFiles is an important part of maintaining Apache Iceberg tables. It allows you to reduce the size of your table by rewriting data files with fewer columns or fewer versions in each file. This can help reduce storage costs and improve performance when querying the table.

Expiring snapshots are used to keep track of changes that have been made to a table over time. They allow you to view a snapshot of the table at any given point in time, which can be useful for auditing purposes or for creating backups before making changes to your table structure or data set.

Managing metadata files is also an important part of maintaining Apache Iceberg tables. Metadata files contain information about the structure and contents of your table, including column names, column types, and partitioning information. They are necessary for querying your table correctly and ensuring that changes you make are reflected in the results you get from queries against your table.

Finally, cleaning up orphan files is essential for keeping your Apache Iceberg tables organized and efficient. Orphan files are those that have been created but never used in any query against the table; they can accumulate over time if not regularly monitored and cleaned up accordingly.

If you're looking for more great content on Data Lakehouse technology, be sure to check out dremio's Subsurface blog! Here you'll find articles on best practices for building Data Lakes using Apache Iceberg as well as other Data Warehouse engines like Hive or PrestoDB. With Subsurface, you'll be able to access all kinds of great content related to Data Lakehouse technology - from tutorials on building Data Lakes with Apache Iceberg to performance tuning tips for optimizing Data Warehouses built with Hive or PrestoDB - all in one convenient place!

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[nooh_jl]

Thank you so much!
I have a question.

I'm wondering if there might be any way to do these procedures automatically in Iceberg.
Do I have to do these things in person every time?

[swaroopsuki]

when we expire the snapshot fi our table created copy-on-write ot merge-on-read the what happen in that case.