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Presentation: Gary Dusbabek (Rackspace) on Cassandra

A presentation about Cassandra given by Rackspace’ Gary Dusbabek (@gdusbabek):

My notes:

What problems does it solve?

  • Reliability at scale
    • No Single point of failure (all nodes are identifical)
  • Simple scaling
    • linear
  • High write thoughput
  • Large data sets

What problems can’t it solve?

  • No flexible indices
  • No querying on non PK values
  • Not good for binary data (>64mb) unless you chunck
  • Row contents must fit in available memory

Concepts: CAP

  • Cassandra chooses A and P but allows them to be tunable to have more C

Data Model

  • Keyspace contains column families
  • ColumnFamily:
    • Standard or Super
    • Two levels of indexes (key and column names)

Data Model

  • Column and subcolumn sorting
  • Specify your own comparator:
    • TimeUUID
    • Lexical UUID
    • UTF8
    • Bytes
    • CreateYourOwn

Inserting: Writes

  • Commit log for durability
  • Memtable - no disk access (no reads or seeks)
  • Sstables are final (become read only)
    • Index
    • Bloom filter
    • Raw data
  • Atomic within a ColumnFamily
  • Bottom line: FAST!!

Note: make sure to check the slide for a nice visual description of Cassandra write operation. You should check also the Cassandra Write operation performance explained for more details.

Querying: Overview

Querying: Reads

  • Not as fast as writes
  • Read repair when out of sync
  • New in 0.6:
    • Row cache (avoid sstable lookup)
    • Key cache (avoid index scan)

Note: make sure you check the slide for a visual description of the Cassandra read operation. And you can also read the Cassandra Reads performance explained for more details.

Future Direction

  • Range delete (delete these cols from those keys)
  • Vector clocks (including server-side conflict resolution)
  • Altering keyspace/column family definitions on a live cluster
  • Byte[] keys
  • Compression
  • Multi-tenant support
  • Less memory restrictions