O V E R V I E W A N D R E A L W O R L D A P P L I C A T I O N S

Cassandra

Jersey Shore Tech Meetup

Nov 13, 2014

You Are Not Here…*** http://njhalloffame.org/

2

Agenda3

Some Basic Concepts/Overview

New Developments In Cassandra

Basic Data Modeling Concepts

Materialized Views

Secondary Indexes

Counters

Time Series Data

Expiring Data

Cassandra High Level4

Cassandra's architecture is based on the combination of two technologies:

Google BigTable – Data Model

Amazon Dynamo – Distributed Architecture

BTW – these mean the same thing ->

Cassandra = C*

Architecture Basics & Terminology5

Nodes are single instances of C*

Cluster is a group of nodes

Data is organized by keys (tokens) which are distributed across the cluster

Replication Factor (rf) determines how many copies are key

Data Center Aware – works well in multi-DC/EC2 etc.

Consistency Level – powerful feature to tune consistency vs. speed vs. availability.’

C* Ring6

More Architecture7

Information on who has what data and who is available is transferred using gossip.

No single point of failure (SPF), every node can service requests.

Handles Replication and Downed Nodes (within reason)

CAP Theorem8

Distributed Systems Law:

Consistency

Availability

Partition Tolerance

(you can only really have two in a distributed system)

Cassandra is AP with Eventual Consistency

Consistency9

Cassandra Uses the concept of Tunable Consistency, which make it very powerful and flexible for system needs.

C* Persistence Model10

Read Path11

Write Path12

Data Model Architecture13

Keyspace – container of column families (tables). Defines RF among others.

Table – column family. Contains definition of schema.

Row – a “record” identified by a key

Column - a key and a value

14

Deletions15

Distributed systems present unique problem for deletes. If it actually deleted data and a node was down and didn’t receive the delete notice it would try and create record when came back online. So…

Tombstone - The data is replaced with a special value called a Tombstone, works within distributed architecture

Keys16

Primary Key

Partition Key – identifies a row

Cluster Key – sorting within a row

Using CQL these are defined together as a compound (composite) key

Compound keys are how you implement “wide rows”, the COOL FEATURE!

Single Primary Key17

create table users (

user_id UUID PRIMARY KEY,

firstname text,

lastname text,

emailaddres text

);

** Cassandra Data Types

http://www.datastax.com/documentation/cql/3.0/cql/cql_ref

erence/cql_data_types_c.html

Compound Key18

create table users (

emailaddress text,

department text,

firstname text,

lastname text,

PRIMARY KEY (emailaddress, department)

);

Partition Key plus Cluster Key

emailaddress is partition key

department is cluster key

Compound Key19

create table users (

emailaddress text,

department text,

country text,

firstname text,

lastname text,

PRIMARY KEY ((emailaddress, department), country)

);

Partition Key plus Cluster Key

Emailaddress & department is partition key

country is cluster key

New Rules20

Writes Are Cheap

Denormalize All You Need

Model Your Queries, Not Data (understand access patterns)

Application Worries About Joins

What’s New In 2.021

Conditional DDL

IF Exists or If Not Exists

Drop Column Support

ALTER TABLE users DROP lastname;

More New Stuff22

Triggers

CREATE TRIGGER myTrigger

ON myTable

USING 'com.thejavaexperts.cassandra.updateevt'

Lightweight Transactions (CAS)UPDATE users

SET firstname = 'tim'

WHERE emailaddress = 'tpeters@example.com'

IF firstname = 'tom';

** Not like an ACID Transaction!!

CAS & Transactions23

CAS - compare-and-set operations. In a single, atomic operation compares a value of a column in the database and applying a modification depending on the result of the comparison.

Consider performance hit. CAS is (was) considered an anti-pattern.

Data Modeling… The Basics24

Cassandra now is very familiar to RDBMS/SQL users.

Very nicely hides the underlying data storage model.

Still have all the power of Cassandra, it is all in the key definition.

RDBMS = model data

Cassandra = model access (queries)

Side-Note On Querying25

Create table with compound key

Select using ALLOW FILTERING

Counts

Select using IN or =

Batch Operations26

Saves Network Roundtrips

Can contain INSERT, UPDATE, DELETE

Atomic by default (all or nothing)

Can use timestamp for specific ordering

Batch Operation Example27

BEGIN BATCH

INSERT INTO users (emailaddress, firstname, lastname, country) values

('brian.enochson@gmail.com', 'brian', 'enochson', 'USA');

INSERT INTO users (emailaddress, firstname, lastname, country) values

('tpeters@example.com', 'tom', 'peters', 'DE');

INSERT INTO users (emailaddress, firstname, lastname, country) values

('jsmith@example.com', 'jim', 'smith', 'USA');

INSERT INTO users (emailaddress, firstname, lastname, country) values

('arogers@example.com', 'alan', 'rogers', 'USA');

DELETE FROM users WHERE emailaddress = 'jsmith@example.com';

APPLY BATCH;

select in cqlsh

List in cassandra-cli with timestamp

More Data Modeling…28

No Joins

No Foreign Keys

No Third (or any other) Normal Form Concerns

Redundant Data Encouraged. Apps maintain consistency.

Secondary Indexes29

Allow defining indexes to allow other access than partition key.

Each node has a local index for its data.

They have uses, but shouldn’t be used all the time without consideration.

We will look at alternatives.

Secondary Index Example30

Create a table

Try to select with column not in PK

Add Secondary Index

Try select again. (maybe need to reinsert)

When to use?31

Low Cardinality – small number of unique values

High Cardinality – high number of distinct values

Secondary Indexes are good for Low Cardinality. So country codes, department codes etc. Not email addresses.

Materialized View32

Want full distribution can use what is called a Materialized View pattern.

Remember redundant data is fine.

Model the queries

Materialized View Example33

Show normal able with compound key and querying limitations

Create Materialized View Table With Different Compound Key, support alternate access.

Selects use partition key.

Secondary indexes local, not distributed

Allow filtering. Can cause performance issues

Counters34

Updated in 2.1 and now work in a more distributed and accurate manner.

Table organization, example

How to update, view etc.

Time Series Example….35

Time series table model.

Need to consider interval for event frequency and wide row size.

Make what is tracked by time and unit of interval partition key.

Time Series Data36

Due to its quick writing model Cassandra is suited for storing time series data.

The Cassandra wide row is a perfect fit for modeling time series / time based events.

Let’s look at an example….

Event Data37

Notice primary key and cluster key.

Insert some data

View in CQL, then in CLI as wide row

TTL – Self Expiring Data38

Another technique is data that has a defined lifespan.

For instance session identifiers, temporary passwords etc.

For this Cassandra provides a Time To Live (TTL) mechanism.

TTL Example…39

Create table

Insert data using TTL

Can update specific column with table

Show using selects.

Questions40

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Email: brian.enochson@gmail.com

Twitter: @benochso

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