Cassandra Synergy

By Niall Milton, DigBigDataPresented to :

Dublin Cassandra User Group

Agenda

What do we mean by synergy?

Storm

Shark / Spark

Redis

ElasticSearch

Hadoop

What do we mean by Synergy?

synergy 1. The interaction of two or more agents or

forces so that their combined effect is greater than the sum of their individual effects.

What do we mean by Synergy?

Cassandra excellent for: Fast read or write performance Scalable, runs on commodity hardware Reliable cross-DC replication Robust persistence for high volume data

Needs some special sauce for: Real-time calculations for high volume streams Complex search functions (free-text etc.) Map Reduce on RDDs

Twitter Storm

Storm

Open Sourced by Twitter in 2011

Distributed event processor

Operates on Resilient Distributed Data Sets

Getting started in Apache Incubator

Can persist to and read from from C*

Great for high volume, real time (complex) calculations on streamed data

Storm

Is a CEP architecture

Spout – Collects & submits tuples for processing

Bolt – processes tuples and emits new tuples

Tuple – a collection of data passed in storm

Stream – identifies outputs from a spout / bolt and enforces tuple structure

Uses Zookeeper and ZeroMQ for coordination and message passing respectively

Example Topology

Synergy?

Can use Cassandra as the input data source

Can write tuples into Cassandra

Example project here… https://github.com/tjake/stormscraper/

See CassandraWriterBolt.java for simple example of a Java Driver CQL based bolt that writes to Cassandra.

Good as an example application, but not production ready

Use Case

Top N words for popularity tracking

Input: a constant stream of messages into the system

Count occurrences of each word in a message

Store raw messages in Cassandra

Use a bolt to break up messages and maintain sorted list of top N words

Persist the Top N words and their counts periodically in Cassandra

Use Case

CREATE TABLE messages (date_hour TIMESTAMP, message_id TIMEUUID, message VARCHAR, PRIMARY KEY(date_hour, message_id));

CREATE TABLE top_words (date_hour TIMESTAMP, position INTEGER, word VARCHAR, PRIMARY KEY(date_hour, position));

Use Case

https://github.com/nathanmarz/storm-starter/

Use RollingTopWords.java as base

Integrate CassandraWriterBolt into use case

Add spout for input messages

Add bolt for persisting messages & writing Top N words

Reference : http://www.michael-noll.com/blog/2013/01/18/implementing-real-time-trending-topics-in-storm/

Storm: Conclusion

Powerful Architecture

Lots of potential as an Apache project

Nice abstractions to simplify development (Trident)

Great for operating on high velocity, high volume streams

Not prohibitively difficult to integrate with other systems for input and output

Lots of people experimenting with it!

Spark & Shark

Lightning fast cluster computing

Apache Spark

100x faster than Hadoop MapReduce!

Faster in-memory MapR operations

Integration with Cassandra either via: https://github.com/tuplejump/calliope-release Or via Cassandra’s Hadoop support

Combines SQL, Streaming and Complex Analytics

Apache Spark

Can read and write to Cassandra…

Reading from CF / Table into RDD via Calliope (Scala)

val cas = CasBuilder.cql3.withColumnFamily("casDemo", "Words”).where("book = 'The Three Musketeers'”)

val rdd = sc.cql3Cassandra[Map[String, String], Map[String, String]](cas)

* where clause can use partition key or secondary index, CasBuilder also supports paging

Shark

With Spark we can achieve super fast in-memory queries on subsets of data in Cassandra

Effectively all the features of Hive running on RDD not HDFS

Uses HiveQL queries

Includes machine learning algorithms out of the box

CqlStorageHandler provided to read RDD from Cassandra or read SSTables directly

https://github.com/richardalow/cassowary

Spark / Shark: Conclusion

Need resource isolation if running directly on Cassandra nodes

Otherwise dealing with higher latency but not affecting cluster resources

Impressive possibilities for machine learning algorithms as well as more basic Hive queries

Introduces possibilities for JOINs on hot data!

REDIS

What is it?

“Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.”

Synergy?

Good for… Sorting sets & lists Pubsub messaging (more) Accurate counters Merging sets Transactions!

Works in memory, can serve data fast based on key

Good for runtime storage of aggregate data

Could use shared resources on Cassandra nodes (could populate most recent data via triggers (naughty))

Elastic Search

Distributed real-time search engine based

What is it?

Distributed real-time search engine

Built from the ground up for reliability and scalability

Supports lots of other features as well free text search Spatial Query by arbitrary fields Facets

Multi-lingual query support

Synergy?

Although external to Cassandra it can provide rich query capabilities over the same data

Simplify Data Models in Cassandra to maximise storage

Separate read and write workloads (read from ES, write to Cassandra)

Some integration for Storm for writing records to elastic search and Cassandra as data enters the system

Again… Spatial!

Hadoop

Batch Analytics

What is it?

Open Source under Apache License 2.0

Top Level Apache project

Runs on commodity hardware

Used for storage and large scale processing of data-sets

Lots of complementary tools… impala, mahout etc.

Some terms…

HDFS a distributed file-system that stores data on

commodity machines, providing very high aggregate bandwidth across the cluster.

Hadoop MapReduce - a programming model for large scale data processing.

Hive - An SQL like abstraction for map reduce jobs

Pig - A procedural style language for expressing map reduce jobs

Synergy?

Multiple ways to use it with Cassandra

DataStax Enterprise supports Hadoop on top of a Cassandra File System Replication managed in-cluster (efficient) Full Hadoop toolset available

Some Hadoop support in vanilla distribution. Limited support for efficient querying

Questions?