How is data read

For a read request, Cassandra consults an in-memory data structure called a Bloom filter that checks the probability of an SSTable having the needed data. The Bloom filter can tell very quickly whether the file probably has the needed data, or certainly does not have it. If answer is a tenative yes, Cassandra consults another layer of in-memory caches, then fetches the compressed data on disk. If the answer is no, Cassandra doesn't trouble with reading that SSTable at all, and moves on to the next.

To satisfy a read, Cassandra must combine results from the active memtable and potentially multiple SSTables. Cassandra processes data at several stages on the read path to discover where the data is stored, starting with the data in the memtable and finishing with SSTables:

• Check the memtable
• Check row cache, if enabled
• Checks Bloom filter
• Checks partition key cache, if enabled
• Goes directly to the compression offset map if a partition key is found in the partition key cache, or checks the partition summary if not If the partition summary is checked, then the partition index is accessed
• Locates the data on disk using the compression offset map
• Fetches the data from the SSTable on disk