Compaction in Cassandra

What is Compaction?

Compaction is a vital process in Apache Cassandra that helps maintain the performance and efficiency of the database. It involves merging multiple SSTables (Sorted String Tables) into a single SSTable, which reduces the number of files that need to be read during queries and helps reclaim disk space used by deleted data.

Why is Compaction Necessary?

As data is written to Cassandra, it is stored in multiple SSTables on disk. Over time, these files can accumulate, leading to increased read latency due to the need to read from multiple SSTables. Compaction addresses this issue by:

• Reducing the number of SSTables on disk
• Reclaiming space from tombstones (deleted data)
• Improving read performance by consolidating data

Types of Compaction Strategies

Cassandra offers several compaction strategies, each suited for different use cases. The most common strategies include:

• SizeTieredCompactionStrategy (STCS): This strategy groups SSTables of similar sizes and compacts them together. It is suitable for write-heavy workloads.
• LeveledCompactionStrategy (LCS): LCS organizes SSTables into levels and allows for more efficient reads by reducing the number of SSTables that need to be checked. It's ideal for read-heavy workloads.
• TimeWindowCompactionStrategy (TWCS): This strategy is designed for time-series data, where data is compacted based on time windows. It is useful for datasets that are mostly written once and read later.

How to Configure Compaction

To configure compaction in Cassandra, you can modify the table's properties using CQL (Cassandra Query Language). Below is an example of how to set the compaction strategy for a table:

This command changes the compaction strategy of the specified table to Leveled Compaction Strategy.

Monitoring Compaction

Monitoring the compaction process is crucial to ensure that it is functioning correctly. You can check the status of compaction using the following command:

This command provides insights into ongoing compaction processes, including the number of SSTables being compacted and the estimated time remaining for completion.

Best Practices for Compaction

To optimize compaction in Cassandra, consider the following best practices:

• Choose the appropriate compaction strategy based on your workload.
• Adjust the compaction throughput settings to balance between write performance and compaction efficiency.
• Regularly monitor compaction metrics using tools like nodetool to identify potential bottlenecks.
• Test different configurations in a staging environment before applying changes in production.