Cassandra basics 2.0
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Cassandra is an open-source, distributed database management system designed to handle large amounts of data across many commodity servers. It provides high availability with no single point of failure, linear scalability and performance as nodes are added, and transparent elasticity allowing addition or removal of nodes without downtime. Data is partitioned and replicated across nodes using consistent hashing to balance loads and ensure availability in the event of failures. The write path sequentially appends data to commit logs and memtables which are periodically flushed to disk as SSTables, while the read path retrieves data from memtables and SSTables in parallel across replicas.
Cassandra basics 2.0
- 1. Introduction to Cassandra Asis Mohanty Source: DataStax, Cassandra
- 2. 01ARCHITECTURE Cassandra Architecture 02 C* CLUSTER Cassandra Cluster 03CQL COLUMN FAMILY CQL Column Family WRITE PATH04 Cassandra Write Path READ PATH05 Cassandra Read Path DATA MODEL 06 C* Data Model Whats is Cassandra?
- 3. • Open-source database management system (DBMS) • Several key features of Cassandra differentiate it from other similar systems Whats is Cassandra?
- 5. Architected Scale in Mind
- 6. What is C* Cluster?
- 7. Peer To Peer
- 8. Data Centers
- 11. Consistent Hashing Consistent hashing allows distributing data across a cluster which minimizes reorganization when nodes are added or removed. Consistent hashing partitions data based on the partition key name age car gender jim 36 camaro M carol 37 bmw F johnny 12 M suzy 10 F For Example Partition key Murmur3 hash value jim -2245462676723223822 carol 7723358927203680754 johnny -6723372854036780875 suzy 1168604627387940318 Cassandra assigns a hash value to each partition key
- 12. What is a CQL table and how is it related to a column family?
- 13. Row is the smallest unit that stores related data in Cassandra • Rows – individual rows constitute a column family • Row key – uniquely identifies a row in a column family • Row – stores pairs of column keys and column values • Column key – uniquely identifies a column value in a row • Column value – stores one value or a collection of values What are row, row key, column key and column value?
- 14. What are partition, partition key, row, column and cell?
- 16. How does Cassandra writes so fast? Cassandra is a log-structured storage engine • Data is sequentially appended, not placed in pre-set locations
- 17. What are the key components of the write path? Each node implements four key components to handle its writes Memtables – in-memory tables corresponding to CQL tables, with indexes CommitLog – append-only log, replayed to restore downed node's Memtables SSTables – Memtable snapshots periodically flushed to disk, clearing heap Compaction – periodic process to merge and streamline SSTables When any node receive any write request The record appends to the CommitLog, and The record appends to the Memtable for this record's target CQL table Periodically, Memtables flush to SSTables, clearing JVM heap and CommitLog Periodically, Compaction runs to merge and streamline SSTables
- 18. How does the write path flow on a node?
- 19. What are Memtables and how are they flushed to disk?
- 20. What is a SSTable and what are its characteristics?
- 21. What is a SSTable and what are its characteristics?
- 24. How does the read path flow on each node?
- 25. How does the read path flow on each node?
- 26. How does the read path flow on each node?
- 27. How does the read path flow on each node?
- 29. What is a data modeling framework?
- 31. What is a conceptual data model?
- 32. Partitioning • Nodes are logically structured in Ring Topology. • Hashed value of key associated with data partition is used to assign it to a node in the ring. • Hashing rounds off after certain value to support ring structure. • Lightly loaded nodes moves position to alleviate highly loaded nodes.
- 33. 33 Appendix
- 34. Consistency – All the servers in the system will have the same data so anyone using the system will get the same copy regardless of which server answers their request. Availability – The system will always respond to a request (even if it's not the latest data or consistent across the system or just a message saying the system isn't working) Partition Tolerance – The system continues to operate as a whole even if individual servers fail or can't be reached.. CAP Theorem
- 35. CassandraArchitecture Overview ○ Cassandra was designed with the understanding that system/ hardware failures can and do occur ○ Peer-to-peer, distributed system ○ All nodes are the same ○ Data partitioned among all nodes in the cluster ○ Custom data replication to ensure fault tolerance ○ Read/Write-anywhere design ○ Google BigTable - data model ○ Column Families ○ Memtables ○ SSTables ○ Amazon Dynamo - distributed systems technologies ○ Consistent hashing ○ Partitioning ○ Replication ○ One-hop routing
- 36. Transparent Elasticity Nodes can be added and removed from Cassandra online, with no downtime being experienced. 1 2 3 4 5 6 1 7 10 4 2 3 5 6 8 9 11 12
- 37. Transparent Scalability Addition of Cassandra nodes increases performance linearly and ability to manage TB’s-PB’s of data. 1 2 3 4 5 6 1 7 10 4 2 3 5 6 8 9 11 12 Performance throughput = N Performance throughput = N x 2
- 38. HighAvailability Cassandra, with its peer-to-peer architecture has no single point of failure.
- 39. Multi-Geography/ZoneAware Cassandra allows a single logical database to span 1-N datacenters that are geographically dispersed. Also supports a hybrid on- premise/Cloud implementation.
- 40. Data Redundancy Cassandra allows for customizable data redundancy so that data is completely protected. Also supports rack awareness (data can be replicated between different racks to guard against machine/rack failures). uses ‘Zookeeper’ to choose a leader which tells nodes the range they are replicas for
- 41. Security in Cassandra • Internal Authentication Manages login IDs and passwords inside the database. • Object Permission Management Controls who has access to what and who can do what in the database Uses familiar GRANT/REVOKE from relational systems. • Client to Node Encryption Protects data in flight to and from a database