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@PatrickMcFadin

Patrick McFadinChief Evangelist/Solution Architect - DataStax

Cassandra 2.0: Better, Stronger, Faster

Thursday, October 3, 13

Five Years of Cassandra

Jul-09 May-10 Feb-11 Dec-11 Oct-12 Jul-13

0.1 0.3 0.6 0.7 1.0 1.2...

2.0

DSE

Jul-08


Cassandra 2.0 - Big new features


SELECT * FROM usersWHERE username = ’jbellis’

[empty resultset]

Session 1SELECT * FROM usersWHERE username = ’jbellis’

[empty resultset]

Session 2

Lightweight transactions: the problem

INSERT INTO users (username,password)VALUES (’jbellis’,‘xdg44hh’)

INSERT INTO users (userName,password)VALUES (’jbellis’,‘8dhh43k’)

It’s a Race!

Who wins?


Client(locks)

Coordinatorrequest

Replica

internalrequest

Why Locking Doesn’t Work

• Client locks•Write times out• Lock released•Hint is replayed!!


Client(locks)

Coordinatorrequest

Replica

internalrequest

X




Client(locks)

Coordinatorrequest

Replica

internalrequest

hint X




Client(locks)

Coordinatorrequest

Replica

internalrequest

hint

timeoutresponse

X




Paxos• Consensus algorithm• All operations are quorum-based• Each replica sends information about unfinished operations to the leader

during prepare• Paxos made Simple


LWT: details• 4 round trips vs 1 for normal updates• Paxos state is durable• Immediate consistency with no leader election or failover• ConsistencyLevel.SERIAL• http://www.datastax.com/dev/blog/lightweight-transactions-in-

cassandra-2-0


http://www.datastax.com/dev/blog/lightweight-transactions-in-cassandra-2-0




LWT: Use with caution• Great for 1% of your application• Eventual consistency is your friend• http://www.slideshare.net/planetcassandra/c-summit-2013-eventual-consistency-

hopeful-consistency-by-christos-kalantzis


http://www.slideshare.net/planetcassandra/c-summit-2013-eventual-consistency-hopeful-consistency-by-christos-kalantzis




UPDATE USERS SET email = ’[email protected]’, ...WHERE username = ’jbellis’IF email = ’[email protected]’;

INSERT INTO USERS (username, email, ...)VALUES (‘jbellis’, ‘[email protected]’, ... )IF NOT EXISTS;

Using LWT

• Don’t overwrite an existing record

• Only update record if condition is met


mailto:[email protected]






Triggers

CREATE TRIGGER <name> ON <table> USING <classname>;

DROP TRIGGER <name> ON [<keyspace>.]<table>;

• Executed on the coordinator before mutation• Takes original mutation and adds any new• Jars deployed per server


Trigger implementationclass MyTrigger implements ITrigger{ public Collection<RowMutation> augment(ByteBuffer key, ColumnFamily update) { ... }}

• You have to implement your own ITrigger (for now)• Compile and deploy to each server


Experimental!• Relies on internal RowMutation, ColumnFamily classes•Not sandboxed. Be careful!• Expect changes in 2.1


CQL Improvements• ALTER DROP• Remove a field from a CQL table

• Conditional schema changes• Only execute if condition met

CREATE KEYSPACE IF NOT EXISTS ksWITH replication = { 'class': 'SimpleStrategy','replication_factor' : 3 };

CREATE TABLE IF NOT EXISTS test (k int PRIMARY KEY);

DROP KEYSPACE IF EXISTS ks;

ALTER TABLE users DROP address3;


CQL Improvements• Aliases in SELECT

• Limit and TTL in prepared statements

SELECT event_id, dateOf(created_at) AS creation_date, blobAsText(content) AS content FROM timeline;

event_id | creation_date | content-------------------------+--------------------------+---------------------- 550e8400-e29b-41d4-a716 | 2013-07-26 10:44:33+0200 | Something happened!?

SELECT * FROM myTable LIMIT ?;

UPDATE myTable USING TTL ? SET v = 2 WHERE k = 'foo';


Cassandra 2.0 - Minor features


Query performance •Hint when reading time series data• Time series slices find data faster

•Hybrid approach to Leveled Compaction under stress• Use size tiered until we catch up• Reduce read latency impact

• Off-heap memory speedup• Bytes moved on and off 10x faster

• Removal of row-level bloom filtersThursday, October 3, 13

Server performance• Single pass compaction• No more incremental compaction for large storage rows

• LMAX Disruptor on Thrift interface• Crazy fast and efficient concurrent threads. Faster HSHA

• Support for pluggable off-heap memory allocators• JEMalloc support to start. Faster memory access.

• Bigger Level 0 file size• 5M was just too small. Now 256M


Removed features• SuperColumns are gone!• Not the API just the underlying implementation

• On-heap row cache• Row cache is no longer an option in the JVM

•Memory pressure relief valves - Gone from yaml• flush_largest_memtables_at

• reduce_cache_sizes_at

• reduce_cache_sizes_to


Operation Changes• JDK 7 now required

• Vnodes are default

• Streaming overhaul• Control. Streams are grouped and broken into plans• Traceability. Each stream has an ID. Monitor each stream.

• Performance. Streams are now pipelined. No waiting for ACK


Thank you!

Apache Cassandra 2.0 - Data model on fire

Next talk in my data model series!


©2013 DataStax Confidential. Do not distribute without consent. 21Thursday, October 3, 13