What is Cassandra Back

  • Cassandra is a ideal database used for social network. It combines Dynamo of Amazon with BitTable of Google, which is based on Column Family(列簇).
  • Official Suggestion: The Apache Cassandra database is the right choice when you need scalability(可擴展性) and high availability without compromising performance.
  • Some characteristics:
    • Dynamo:
      • Symmetric(對稱的) P2P framework
        • Without special node(solving the problem of SPOF(單點失效))
      • Distributed Management based on Gossip
      • Store data with distributed hash tables.
        • pluggable partition(可插拔分區)
        • pluggable topologies(可插拔拓撲)
        • pluggable store strategies(可插拔存放策略)
      • Configurable(eventual consistency)
    • BigTable:
      • Column Family Data Model
        • configurable, 2-levels maps, super column family
      • SSTable
        • Append-only commit log
        • Memtable(buffer and sort)
        • Unmodifiable SSTable files
      • Integrated Hadoop

Data Model

  • Column: the minimum components of a data, and it's composed of Name, Value, and Timestamp.
  • Notice: name and value should be byte[], which a string of any length.
    "name": "email",
    "value": "aleen42@vip.qq.com",
    "timestamp": 1455517240
  • SuperColumn: the name is same as Column, while the value is a set of columns. In additionally, they don't have timestamps.
    "name": "addresses",
    "value": {
        "street": { "name": "street", "value": "xxx xxx xxx Road", "timestamp": 1455517515 },
        "city": { "name": "city", "value": "Foshan", "timestamp": 1455517515 },
        "zip": { "name": "zip", "value": "528031", "timestamp": 1455517515 }
  • Both SuperColumn Family and Column Family describe a set of SuperColumn and Column.
  • Sorting:
    • Notice: in Cassandra, data is sorted by Column name by default.
    • Configurable:
      • Set CompareWith Attribute (Column Family)
      • Set CompareSubColumnsWith (SuperColumn Family)
    • Value for configuration:
      • BytesType
      • UTF8Type
      • LexicalUUIDType
      • TimeUUIDType
      • AsciiType
      • Column name

Partition Strategies

  • In Cassandra, Token is the key point for partitions, and there is a unique token for each node, describing the range of data in which. All the tokens will be stored as a ring(Cassandra Ring), and use hash value to calculate.
  • There are 3 strategies for partitions in Cassandra:
    • Random Partitioner:
      • Token will be a BitInteger(0 ~ 2127), mapped with hash. (In Cassandra, it will take a 128 bits MD5 absolute value, which contains a sign bit)
      • In a in-extreme(極端的) situation, it can map 2127 + 1 nodes.
      • Notice: it's not supported that searching data with key in this strategic.
    • Order Preserving Partitioner(ordered):
      • Token will be a string.
      • It depends on the key to certain which nodes to be chosen
      • Notice: without Initial Token, system will take a 16 bits random strings which contain numbers and alphabets as the token.
    • Collating Order Preserving Partitioner(ordered):
      • Token will be a byte.
      • Configurable sorting in different languages(en_US by default)
  • Partition strategies and Token(including Initial Token) can be set in the file storage-conf.xml.

Bloom Filter

  • Bloom Filter is a random data structure, saving huge space by sacrificing precision. (This structure cannot be applied to applications which are sensitive to accuracy.)
  • In Cassandra, each key-value pair will use one byte to complete Bloom Filter.
  • Read more details in Wikipedia

Storage Strategies

  • In Cassandra, data will be stored in the local file system of each node with 3 strategic to copy data:
    • Simple Strategy(RackUnaware Strategy): copies will be saved in the next several nodes behind this node.
    • OldNetwork Topology Strategy(RackAware Strategy): one copy will be saved in a different node, while other N - 2 copies will be saved in other machines in the same node.
    • Network Topology Strategy: M copies will be saved in different nodes, while N - M - 1 copies will be saved in different machines of the same node.
  • Storage mechanisms:
    • Commit Log: Cassandra will log records when writing data like HBase. After logging, data will be written into memtable and flushed into the SSTable, which is read-only once written into. (In Cassandra, there is no random write)
    • Memtable: when data has reached the size of a block, it will be flushed into the disk, and stored as SSTable.
    • SSTable: it's read-only and one CF will be corresponding with several SSTable. Bloom Filter will be used to justify which SSTable the key belongs to.
      • Compaction used in Cassandra:
        • Garbage Collect: delete the data which is really signed.
        • Merge SSTable in the same CF.
        • Generate a Merkle Tree.
  • Read more details in IBM documents


  • Sniffing is mainly used to calculate the distance between different host to tell Cassandra what the topology looks like. There are 3 strategies to configure:
    • org.apache.cassandra.locator.SimpleSnitch: logical distance(the difference between Cassandra Ring)
    • org.apache.cassandra.locator.RackInferringSnitch: the distance depends on rack(the third 8 bits in IP) and data center(the second 8 bits in IP)
    • org.apache.cassandra.locator.PropertyFileSnitch: the distance depends on rack and data center, which are both configured in the configuration file, cassandra-topology.properties.


  • Eventual Consistency is used in Cassandra. Users can choose different level of consistency to use.

  • Notice: the level of consistency depends on the number of copies instead of the number of nodes.
Quorum NRW
  • N: means the number of copies once(In generally, N > 3 in a distributed system to ensure fault-tolerance)
  • R: means the minimum of nodes which is successful to read once
  • W: means the minimum of nodes which is successful to write once
  • In Quorum, consistency will be strong when W + R > N, but availability will be low.
  • In Quorum, consistency will be weak when W + R <= N, but availability will be high. (This will be used generally when eventual consistency is guaranteed)

  • In Cassandra, there are 4 methodologies to ensure eventual consistency:

    • Anti-Entropy(逆熵): the mothod used to check consistency called Merkle Tree.
    • Read Repair: repair in the case that finding it's not consistent when reading data from key A and all the copies of key A.
      • ONE: return a recent copy immediately, and repair in the background. (The first data you read will not be the latest one)
      • QUORUM: return a copy when there is no problems after checking more than half of all copies, and check remaining copies and repair if necessary in the background.
      • ALL: return a copy when there is no problems after checking all.
    • Hinted Handoff(提示提交): write to a relay node when the target is offline, and the relay node will wait for the target to complete writing.
    • Distributed Delete: Cassandra will sign a hint to the object which is deleted by other nodes, and this object will be collected when doing Garbage Collect at the fixed time.
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