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The "LargeDataSetConsiderations" page has been changed by PeterSchuller. http://wiki.apache.org/cassandra/LargeDataSetConsiderations?action=diff&rev1=1&rev2=2 -------------------------------------------------- Unless otherwise noted, the points refer to Cassandra 0.7 and above. + * As your data set becomes larger and larger (assuming significantly larger than memory), you become more and more dependent on caching to elide I/O operations. As you plan and test your capacity, keep min mind that: + * The cassandra row cache is in the JVM heap and un-affected (remains warm) by compactions and repair operations. + * The key cache is affected by compaction and repair. + * Soon no longer true as of: TODO: insert jira ticket link + * The operating system's page cache is affected by compaction and repair operations. If you are relying on the page cache to keep the active set in memory, you may see significant degradation on performance as a result of compaction and repair operations. + * There is work happening to improve this. TODO: link to JIRA tickets about direct i/o, fadvise, mincore() etc. * If you have column families with more than 143 million row keys in them, bloom filter false positive rates are likely to go up because of implementation concerns that limit the maximum size of a bloom filter. See [[ArchitectureInternals]] for information on how bloom filters are used. The negative effects of hitting this limit is that reads will start taking additional seeks to disk as the row count increases. Note that the effect you are seeing at any given moment will depend on when compaction was last run, because the bloom filter limit is per-sstable. It is an issue for column families because after a major compaction, the entire column family will be in a single sstable. * This will likely be addressed in the future: TODO: add JIRA links to the bigger-bf and the limit-sstable-size issue. * Compaction is currently not concurrent, so only a single compaction runs at a time. This means that sstable counts may spike during larger compactions as several smaller sstables are written while a large compaction is happening. This can cause additional seeks on reads.
