Apache cassandra
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This document provides an overview of Apache Cassandra including its history, architecture, data modeling concepts, and how to install and use it with Python. Key points include that Cassandra is a distributed, scalable NoSQL database designed without single points of failure. It discusses Cassandra's architecture including nodes, datacenters, clusters, commit logs, memtables, and SSTables. Data modeling concepts explained are keyspaces, column families, and designing for even data distribution and minimizing reads. The document also provides examples of creating a keyspace, reading data using Python driver, and demoing data clustering.
![What is Apache Cassandra?
• According to Wikipedia:
Apache Cassandra is a free and open-source,
distributed, wide column store, NoSQL 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,[1] with
asynchronous masterless replication allowing low
latency operations for all clients.](https://image.slidesharecdn.com/apachecassandra-190522012425/85/Apache-cassandra-2-320.jpg)
![Reading Data
from cassandra.cluster import Cluster
if __name__ == "__main__":
cluster = Cluster(['0.0.0.0'],port=9042)
session =
cluster.connect('cityinfo',wait_for_all_pools=T
rue)
session.execute('USE cityinfo')
rows = session.execute('SELECT * FROM
users')
for row in rows:
print(row.age,row.name,row.username)](https://image.slidesharecdn.com/apachecassandra-190522012425/85/Apache-cassandra-30-320.jpg)
Apache cassandra
- 1. Getting started with Apache Cassandra and Python By Adnan Siddiqi (http://adnansiddiqi.me)
- 2. What is Apache Cassandra? • According to Wikipedia: Apache Cassandra is a free and open-source, distributed, wide column store, NoSQL 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,[1] with asynchronous masterless replication allowing low latency operations for all clients.
- 3. History • Developed by two Facebook engineers to deal with search mechanism of Inbox. • Released as an open-source project after few years. • Handed over to Apache Foundation.
- 4. Companies using Cassandra • Apple • Netflix • eBay • Weather Channel
- 5. Architecture
- 6. Architecture(Contd…) • Node:- The basic component of the data, a machine where the data is stored. • Datacenter:- A collection of related nodes. It can be a physical datacenter or virtual. • Cluster:- A cluster contains one or more datacenters, it could span across locations. • Commit Log:- Every write operation is first stored in the commit log. It is used for crash recovery.
- 7. Architecture(Contd…) • Mem-Table:- After data is written to the commit log it then is stored in Mem- Table(Memory Table) which remains there till it reaches to the threshold. • SSTable:- Sorted-String Table or SSTable is a disk file which stores data from MemTable once it reaches to the threshold. SSTables are stored on disk sequentially and maintained for each database table.
- 9. Write Operations(Contd…) • Write request is stored in both CommitLog to make sure that data is saved. • Data is written in Memtable which holds data till it reaches to threshold. • Data is flused to SSTable once Memtable reaches to its threshold. • The node that accepts requests called Coordinator.
- 10. Read Operations • Direct Request:- The coordinator node sends the read request to one of the replicas. • Digest:- The coordinator contacts the replicas specified by the consistency level. The contacted nodes respond with a digest request of the required data. Comparison takes place to make sure that the update data is sent back.
- 11. Replication Strategies • Simple Strategy • Network Topology
- 12. Simple Strategy • It is used when you have only one data center. It places the first replica on the node selected by the partitioner. A partitioner determines how data is distributed across the nodes in the cluster (including replicas). After that, remaining replicas are placed in a clockwise direction in the Node ring.
- 14. Network Topology Strategy • Deployments across multiple Datacenters. • This strategy places replicas in the same datacenter by traversing the ring clockwise until reaching the first node in another rack. • This strategy is highly recommended for scalability purpose and future expansion.
- 16. Installation and Setup • Dockerized Version. • docker pull cassandra • Make sure to set the Docker memory to 4GB atleast to avoid 137 exit error code.
- 17. Installation and Setup(Contd…) • data docker exec -it cas1 nodetool status
- 18. CQL Shell
- 19. GUI Client
- 22. Cassandra Data Modeling • Keyspace:- It is the container collection of column families. You can think of it as a Database in the RDBMS world. • Column Family:- A column family is a container for an ordered collection of rows. Each row, in turn, is an ordered collection of columns. Think of it as a Table in the RDBMS world.
- 25. Creating KeySpace • Creating Keyspace with name CityInfo. • create keyspace CityInfo with replication = {'class' : 'SimpleStrategy', 'replication_factor':2}
- 26. Designing Modeling Goals • Evenly spread of data in a cluster. • Minimize the number of Reads.
- 27. Demo
- 28. Data Clustering
- 29. Cassandra and Python • pip install cassandra-driver
- 30. Reading Data from cassandra.cluster import Cluster if __name__ == "__main__": cluster = Cluster(['0.0.0.0'],port=9042) session = cluster.connect('cityinfo',wait_for_all_pools=T rue) session.execute('USE cityinfo') rows = session.execute('SELECT * FROM users') for row in rows: print(row.age,row.name,row.username)
- 31. The End