1. Cassandra 2.0
!
!
Michael Shaler!
Senior Director, Applications Business
©2013 DataStax Confidential. Do not distribute without consent.

2. Open Source Database Pedigrees
MemcacheDB
Azure Table Services
Key Value
Stores
Redis
Tokyo Cabinet
SimpleDB
Riak
Amazon
Dynamo
Voldemort
Google
BigTable
Cassandra
Hbase
Hypertable
CouchDB
Document DB
UserGrid
MongoDB
JSON/XML DB
Neo4J
Graph
Databases
TitanDB
FlockDB
* Courtesy of @GuyHarrison

3. Common Use Cases
cassandra
•
Web product searches !
•
Internal document search (law firms, etc.)!
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Real estate/property searches !
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Social media match ups!
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Web & application log management / analysis
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Big data OLTP and write intensive systems!
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Time series data management!
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High velocity device data consumption and analysis!
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Healthcare systems input and analysis!
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Media streaming (music, movies, etc.)!
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Social media input and analysis!
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Online Web retail (shopping carts, user transactions, etc.)!
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Web click-stream analysis !
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Online gaming (real-time messaging, etc.)
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Buyer event and behavior analytics!
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Real time data analytics
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Fraud detection and analysis!
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Risk analysis and management !
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Supply chain analytics !
!
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4. Cassandra as Foundation
Benefit
Feature
Fully Distributed: no SPOF
Peer-to-peer architecture for continuous availability and
operational simplicity
Multi-Datacenter
Node-, rack- and DC-aware with tunable consistency
Massively Scalable
Multiple customers > 10M writes/second
SSD and Cloud optimized
All writes are linear, and all files are immutable
Rich Application Data Model
CQL (no joins or 2PC), integration with ODBC/JDBC et al

5. What’s New in Cassandra 2.0
• Lightweight Transactions!
-IF keyword in CQL INSERT and UPDATE statements!
-SERIAL consistency level!
• Triggers!
-Phase 1 support!
• CQL paging support!
• Prepared statement support: Atomic BATCH guarantees!
• Bind variable support!
• Improved authentication via SASL!
• Drop column support (ALTER TABLE DROP)!
• SELECT column aliases!
• Conditional DDL!
• Index enhancements!
• One-off prepare and execute statements!
• Performance enhancements!
-Off-heap partition summary!
-Eager retries support!
-Compaction improvements
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6. C* 2.0 Feature Highlights
• Lightweight transactions !
• Triggers (experimental)!
• Improved compaction!
• CQL cursors
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7. The Problem: Sometimes we need Serializablity
Session 1
Session 2
SELECT * FROM users
WHERE username = ’jbellis’
[empty resultset]
INSERT INTO users (...)
VALUES (’jbellis’, ...)
SELECT * FROM users
WHERE username = ’jbellis’
[empty resultset]
INSERT INTO users (...)
VALUES (’jbellis’, ...)
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8. LWT: Details
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•
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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
•
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9. Paxos for LWT
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10. LWT: Use sparingly, with caution
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Great for 1% of your application
Eventual consistency is your
friend
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http://www.slideshare.net/
planetcassandra/c-summit-2013eventual-consistency- hopefulconsistency-by-christos-kalantzis
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11. LWT example
INSERT INTO USERS (username, email, ...)
VALUES (‘jbellis’,
‘jbellis@datastax.com’, ... )
IF NOT EXISTS;
!
UPDATE USERS
SET email = ’jonathan@datastax.com’, ...
WHERE username = ’jbellis’
IF email = ’jbellis@datastax.com’;
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12. Some fine print…:)
• The columns updated do NOT have to be the same as the columns in the IF
clause.
• Lightweight transactions are restricted to a single partition; this is the
granularity at which we keep the internal Paxos state. As a corollary,
transactions in different partitions will never interrupt each other.
• If your transaction fails because the existing values did not match the one you
expected, Cassandra will include the current ones so you can decide whether
to retry or abort without needing to make an extra request.
• ConsistencyLevel.SERIAL has been added to allow reading the current
(possibly un-committed) Paxos state without having to propose a new update.
If a SERIAL read finds an uncommitted update in progress, it will commit it as
part of the read.
• For details of how we deal with failures, see the comments and code.
• Tickets for DC-local transactions, updating multiple rows in a transaction, and
cqlsh support for retrieving the current value from an interrupted transaction
are open and will be fixed for 2.0.1.
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13. Triggers
CREATE TRIGGER <name> ON <table>
USING <classname>;
!
class MyTrigger implements ITrigger
{
public Collection<RowMutation>
augment(ByteBuffer key, ColumnFamily update)
{
}
}
...
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14. Triggers are EXPERIMENTAL!
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Relies on internal
RowMutation,
ColumnFamily classes
[partition] key is a ByteBuffer
Expect changes in 2.1
•
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15. Compaction
• Single-pass, always
• LCS performs STCS in L0
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16. Healthy Leveled Compaction
ealthy leveled compaction
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17. ad leveled compaction
Sad Leveled Compaction
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18. STCS in L0
STCS in L0
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19. Cursors (before)
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CREATE TABLE timeline (
user_id uuid,
tweet_id timeuuid,
tweet_author uuid,
tweet_body text,
PRIMARY KEY (user_id, tweet_id)
);
!
SELECT *
FROM timeline
WHERE (user_id = :last_key
AND tweet_id > :last_tweet)
OR token(user_id) > token(:last_key)
LIMIT 100
•
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20. Cursors (before)
!
CREATE TABLE timeline (
user_id uuid,
tweet_id timeuuid,
tweet_author uuid,
tweet_body text,
PRIMARY KEY (user_id, tweet_id)
);
!
SELECT *
FROM timeline
WHERE (user_id = :last_key
AND tweet_id > :last_tweet)
OR token(user_id) > token(:last_key)
LIMIT 100
•
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21. Other Performance Improvements
• Tracking statistics on clustered columns allows eliminating
unnecessary sstables from the read path
• New half-synchronous, half-asynchronous Thrift server
based on LMAX Disruptor
• Faster partition index lookups and cache reads by improving
performance of off-heap memory
• Faster reads of compressed data by switching from CRC32
to Adler checksums
• JEMalloc support for off-heap allocation
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22. Clean-up
• Removed compatibility with pre-1.2.5 sstables and pre-1.2.9
schema
• The potentially dangerous countPendingHints JMX call has been
replaced by a Hints Created metric
• The on-heap partition cache (“row cache”) has been removed
• Vnodes are on by default
The old token range bisection code for non-vnode clusters is gone
• Removed emergency memory pressure valve logic
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23. Operational Considerations
• Java7 is now required!
• Leveled compaction level information has been moved
into sstable metadata
• Kernel page cache skipping has been removed in favor
of optional row preheating (preheat_kernel_page_cache)
• Streaming has been rewritten to be more transparent
and robust.
• Streaming support for old-version sstables
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24. Questions?!
!
Answers?
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