Cassandra Architecture

Cassandra Architecture

Cassandra Architecture

Apache Cassandra is an open source distributed database management system designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure. Cassandra offers robust support for clusters spanning multiple datacenters, with asynchronous masterless replication allowing low latency operations for all clients.

Cassandra stores data on different nodes with a peer to peer distributed fashion architecture.

All the nodes exchange information with each other using Gossip protocol. Gossip is a protocol in Cassandra by which nodes can communicate with each other.

Components of Cassandra

Components of Cassandra

  • Node, where data is stored

  • Data Center, Collection of nodes

  • Cluster, collection of datacenters

  • Commit Log, write operation is written to Commit Log. Commit log is used for crash recovery.

  • Mem-table, data written in Commit log is written in Mem-table temporarily.

  • SSTable, When Mem-table reaches a certain threshold, data is flushed to an SSTable disk file.

Life cycle of the data

CommitLog, MemTable, and SSTable are 3 core components of cassandra.

High level life cycle of the data from the time it is written from a cassandra client to the time it is persisted to SSTables

Lifecycle of Data

Step 1 Request is received by a random node in the cluster.

Step 2 Node Writes data into the local commit log file in a sequential manner.

Step 3 Memtable gets updated in asynchronous mode.

Step 4 Memtable flushes the data to SSTables periodically, SStables is really the final persistance store for the data.

Step 5 Once data makes it way to SSTables the corresponding reference of the record in commit log and Memtable is flushed out.


  • Used for maintenance, to ensure all pending transactions are flushed out to the SSTables before a node shutdown

  • Explicitly flush the data in commit log or Mem-tableinto SSTable

Testing Cassandra Durability

  • Create a single node cluster
  • Let us put cassandra’s durability to test with a real world ecommerce use case.
  • Let us assume we have a keyspace that manages user cart or orders and given a scenario of node failure let us put cassandra’s durability to test.

  • Load some sample data into cassandra and shutdown the databased before cassandra performs a flush to SSTables.

  • Make sure cassandra server is running, start by using following command in the foreground

Write Operation

The coordinator sends a write request to replicas. If all the replicas are up, they will receive write request regardless of their consistency level.

Consistency level determines how many nodes will respond back with the success acknowledgment.

The node will respond back with the success acknowledgment if data is written successfully to the commit log and memTable.



docker exec it <CONTAINER_NAME> bash
# create keyspace
CREATE KEYSPACE ecommerce WITH replication = {'class':'SimpleStrategy', 'replication_factor':3};

-- create table
CREATE TABLE ecommerce.orders (
           users_id INT,
           orders_id INT,
           order_status text,
           first_name text,
           last_name text,
           order_total float, 
           shipping_total float, 
           tax_total float, 
           promotions_total float,
           emails set<text>,
           order_log map<text, timestamp>,
           order_comments map<text, timestamp>,
           PRIMARY KEY(orders_id, users_id)
) WITH comment='Orders Table';

# insert sample data
INSERT INTO ecommerce.orders (users_id, orders_id, order_status, first_name, last_name, order_total, shipping_total, tax_total, promotions_total, emails,order_log,order_comments)
       VALUES(123, 321,'Pending' ,'hariharan','vadivelu',20.30,2.00,1.00,5.00,{'', ''},{ 'created_on':'2013-06-13 11:42:12','last_updated':'2013-06-13 11:42:12'},{ 'comment_1':'2013-06-13 11:42:12','comment_2':'2013-06-13 11:42:12'});

INSERT INTO ecommerce.orders (users_id, orders_id, order_status, first_name, last_name, order_total, shipping_total, tax_total, promotions_total, emails,order_log,order_comments)
       VALUES(1234, 4321,'Pending' ,'hariharan','vadivelu',20.30,2.00,1.00,5.00,{'', ''},{ 'created_on':'2013-06-13 11:42:12','last_updated':'2013-06-13 11:42:12'},{ 'comment_1':'2013-06-13 11:42:12','comment_2':'2013-06-13 11:42:12'});

Once the data is loaded you can exit cqlsh and check your data directory, the location of data directory is defined in ./config/cassandra.yaml files “data_file_directories” key property.

E..g if mapped to your home directory, go to ~/cassandra/data/ecommerce/orders and you should not notice any files in this directory, usually you will find a couple of files related to SSTables in this location once the flush operation is completed.

We can terminate cassandra at this point to replicate a situation where in cassandra data is not yet flused to SSTables and is only available with in the commit log and Memtables in memory data store.

Now you can bring up cassandra and you should notice few interesting log messages indicating a replay of pending records from commit log to SSTables. Once this operation is complete check the ~/cassandra/data/ecommerce/orders folders and you should not see the data inserted before the server crash.

Completed flushing /home/search/cassandra/data/system/compaction_history/system-compaction_history-jb-1-Data.db (237 bytes) for commitlog position ReplayPosition(segmentId=1395543674692, position=271)

You should be able to query the same from cqlsh as well.

select * from ecommerce.orders;

or you can also check the data in sstables using the ./bin/sstables utility

./sstable2json /home/search/cassandra/data/ecommerce/orders/ecommerce-orders-jb-1-Data.db

Read Operation

There are three types of read requests that a coordinator sends to replicas

  • Direct request
  • Digest request
  • Read repair request

The coordinator sends direct request to one of the replicas. After that, the coordinator sends the digest request to the number of replicas specified by the consistency level and checks whether the returned data is an updated data.

After that, the coordinator sends digest request to all the remaining replicas. If any node gives out of date value, a background read repair request will update that data. This process is called read repair mechanism.

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