ScyllaDB is a high-performance, distributed NoSQL database designed to handle large volumes of data with low latency. It is compatible with Apache Cassandra and offers superior performance by leveraging a modern architecture that takes full advantage of multi-core processors and large memory footprints. ScyllaDB is used in various applications where scalability and speed are critical, such as real-time analytics, IoT, and time-series data processing.
One of the common issues encountered in ScyllaDB is a compaction failure. This issue is typically observed when the database logs indicate that the compaction process has failed. Users may notice increased disk usage, degraded performance, or receive error messages related to compaction failures.
Compaction is a critical process in ScyllaDB that merges multiple SSTables into a single SSTable, reducing the number of files and reclaiming disk space. However, compaction can fail due to:
Failure in compaction can lead to increased read and write latencies, higher disk usage, and potential data inconsistency if not addressed promptly.
To resolve compaction failures in ScyllaDB, follow these steps:
Ensure that there is sufficient disk space available for the compaction process. You can free up space by:
Run disk checks to ensure there are no underlying hardware issues. Use tools like fsck on Linux to check and repair disk errors.
If SSTables are suspected to be corrupted, use the nodetool scrub command to repair them:
nodetool scrub <keyspace> <table>
This command will attempt to fix any corruption in the SSTables for the specified keyspace and table.
For more information on managing ScyllaDB and handling compaction issues, refer to the following resources:
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