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@doanduyhai
Cassandra & Spark, closing the gap
between NoSQL and analytics
DuyHai DOAN, Technical Advocate
@doanduyhai
Who Am I ?
Duy Hai DOAN
Cassandra technical advocate
•  talks, meetups, confs
•  open-source devs (Achilles, …)
•  OSS Cassandra point of contact
☞ duy_hai.doan@datastax.com
☞ @doanduyhai
2
@doanduyhai
Datastax
•  Founded in April 2010
•  We contribute a lot to Apache Cassandra™
•  400+ customers (25 of the Fortune 100), 400+ employees
•  Headquarter in San Francisco Bay area
•  EU headquarter in London, offices in France and Germany
•  Datastax Enterprise = OSS Cassandra + extra features
3
@doanduyhai
Spark – Cassandra Use Cases
Load data from various
sources
Analytics (join, aggregate, transform, …)
Sanitize, validate, normalize, transform data
Schema migration,
Data conversion
4
Spark & Cassandra Presentation
Spark & its eco-system
Cassandra Quick Recap
@doanduyhai
What is Apache Spark ?
Created at
Apache Project since 2010
General data processing framework
Faster than Hadoop, in memory
One-framework-many-components approach
6
@doanduyhai
Partitions transformations
map(tuple => (tuple._3, tuple))
Direct transformation
Shuffle (expensive !)
groupByKey()
countByKey()
partition
RDD
Final action
7
@doanduyhai
Spark eco-system
Local Standalone cluster YARN Mesos
Spark Core Engine (Scala/Java/Python)
Spark Streaming MLLibGraphXSpark SQL
Persistence
Cluster Manager
…
etc…
8
@doanduyhai
Spark eco-system
Local Standalone cluster YARN Mesos
Spark Core Engine (Scala/Java/Python)
Spark Streaming MLLibGraphXSpark SQL
Persistence
Cluster Manager
…
etc…
9
@doanduyhai
What is Apache Cassandra?
Created at
Apache Project since 2009
Distributed NoSQL database
Eventual consistency
Distributed table abstraction
10
@doanduyhai
Cassandra data distribution reminder
Random: hash of #partition → token = hash(#p)
Hash: ]-X, X]
X = huge number (264/2)
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@doanduyhai
Cassandra token ranges
A: ]0, X/8]
B: ] X/8, 2X/8]
C: ] 2X/8, 3X/8]
D: ] 3X/8, 4X/8]
E: ] 4X/8, 5X/8]
F: ] 5X/8, 6X/8]
G: ] 6X/8, 7X/8]
H: ] 7X/8, X]
Murmur3 hash function
n1
n2
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n8
A
B
C
D
E
F
G
H
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@doanduyhai
Linear scalability
n1
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A
B
C
D
E
F
G
H
user_id1
user_id2
user_id3
user_id4
user_id5
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@doanduyhai
Linear scalability
n1
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A
B
C
D
E
F
G
H
user_id1
user_id2
user_id3
user_id4
user_id5
14
@doanduyhai
Cassandra Query Language (CQL)
INSERT INTO users(login, name, age) VALUES(‘jdoe’, ‘John DOE’, 33);
UPDATE users SET age = 34 WHERE login = ‘jdoe’;
DELETE age FROM users WHERE login = ‘jdoe’;
SELECT age FROM users WHERE login = ‘jdoe’;
15
Spark & Cassandra Connector
Spark Core API
SparkSQL/DataFrame
Spark Streaming
@doanduyhai
Spark/Cassandra connector architecture
All Cassandra types supported and converted to Scala types
Server side data filtering (SELECT … WHERE …)
Use Java-driver underneath
Scala and Java support. Python support via PySpark (exp.)
17
@doanduyhai
Connector architecture – Core API
Cassandra tables exposed as Spark RDDs
Read from and write to Cassandra
Mapping of C* tables and rows to Scala objects
•  CassandraRDD and CassandraRow
•  Scala case class (object mapper)
•  Scala tuples
18
@doanduyhai
Spark Core
https://github.com/doanduyhai/incubator-zeppelin/tree/ApacheBigData
@doanduyhai
Connector architecture – DataFrame
Mapping of Cassandra table to DataFrame
•  CassandraSQLContext à org.apache.spark.sql.SQLContext
•  CassandraSQLRow à org.apache.spark.sql.catalyst.expressions.Row
•  Mapping of Cassandra types to Catalyst types
•  CassandraCatalog à Catalog (used by Catalyst Analyzer)
20
@doanduyhai
Connector architecture – DataFrame
Mapping of Cassandra table to SchemaRDD
•  CassandraSourceRelation
•  extends BaseRelation with InsertableRelation with PruntedFilteredScan
•  custom query plan
•  push predicates to CQL for early filtering (if possible)
SELECT * FROM user_emails WHERE login = ‘jdoe’;
21
@doanduyhai
Spark SQL
https://github.com/doanduyhai/incubator-zeppelin/tree/ApacheBigData
@doanduyhai
Connector architecture – Spark Streaming
Streaming data INTO Cassandra table
•  trivial setup
•  be careful about your Cassandra data model when having an infinite
stream !!!
Streaming data OUT of Cassandra tables (CASSANDRA-8844) ?
•  notification system (publish/subscribe)
•  at-least-once delivery semantics
•  work in progress …
23
@doanduyhai
Spark Streaming
https://github.com/doanduyhai/incubator-zeppelin/tree/ApacheBigData
@doanduyhai
Q & R
! "
Spark/Cassandra operations
Cluster deployment & job lifecycle
Data locality
@doanduyhai
Cluster deployment
C*
SparkM
SparkW
C*
SparkW
C*
SparkW
C*
SparkW
C*
SparkW
Stand-alone cluster
27
@doanduyhai
Cassandra – Spark placement
Spark Worker Spark Worker Spark Worker Spark Worker
1 Cassandra process ⟷ 1 Spark worker
C* C* C* C*
28
Spark Master
@doanduyhai
Cassandra – Spark job lifecycle
Spark Worker Spark Worker Spark Worker Spark Worker
C* C* C* C*
29
Spark Master
Spark Client
Driver Program
Spark Context
1
D e f i n e y o u r
business logic
here !
@doanduyhai
Cassandra – Spark job lifecycle
Spark Worker Spark Worker Spark Worker Spark Worker
C* C* C* C*
30
Spark Master
Spark Client
Driver Program
Spark Context
2
@doanduyhai
Cassandra – Spark job lifecycle
Spark Worker Spark Worker Spark Worker Spark Worker
C* C* C* C*
31
Spark Master
Spark Client
Driver Program
Spark Context
3 333
@doanduyhai
Cassandra – Spark job lifecycle
Spark Worker Spark Worker Spark Worker Spark Worker
C* C* C* C*
32
Spark Master
Spark Client
Driver Program
Spark Context
Spark Executor Spark Executor Spark Executor Spark Executor
444 4
@doanduyhai
Cassandra – Spark job lifecycle
Spark Worker Spark Worker Spark Worker Spark Worker
C* C* C* C*
33
Spark Master
Spark Client
Driver Program
Spark Context
Spark Executor Spark Executor Spark Executor Spark Executor
5 5 5 5
@doanduyhai
Data Locality – Cassandra token ranges
A: ]0, X/8]
B: ] X/8, 2X/8]
C: ] 2X/8, 3X/8]
D: ] 3X/8, 4X/8]
E: ] 4X/8, 5X/8]
F: ] 5X/8, 6X/8]
G: ] 6X/8, 7X/8]
H: ] 7X/8, X]
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A
B
C
D
E
F
G
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34
@doanduyhai
Data Locality – How To
C*
SparkM
SparkW
C*
SparkW
C*
SparkW
C*
SparkW
C*
SparkW
Spark partition RDD
Cassandra
tokens ranges
35
@doanduyhai
Data Locality – How To
C*
SparkM
SparkW
C*
SparkW
C*
SparkW
C*
SparkW
C*
SparkW
Use Murmur3Partitioner
36
@doanduyhai
Read data locality
Read from Cassandra
37
@doanduyhai
Read data locality
Spark shuffle operations
38
@doanduyhai
Write to Cassandra without data locality
Async batches fan-out writes to Cassandra
Because of shuffle, original data locality is lost
39
@doanduyhai
Write to Cassandra with data locality
Write to Cassandra
rdd.repartitionByCassandraReplica("keyspace","table")
40
@doanduyhai
Write data locality
•  either stream data in Spark layer using repartitionByCassandraReplica()
•  or flush data to Cassandra by async batches
•  in any case, there will be data movement on network (sorry no magic)
41
@doanduyhai
Joins with data locality
CREATE TABLE artists(name text, style text, … PRIMARY KEY(name));
CREATE TABLE albums(title text, artist text, year int,… PRIMARY KEY(title));
val join: CassandraJoinRDD[(String,Int), (String,String)] =
sc.cassandraTable[(String,Int)](KEYSPACE, ALBUMS)
// Select only useful columns for join and processing
.select("artist","year")
.as((_:String, _:Int))
// Repartition RDDs by "artists" PK, which is "name"
.repartitionByCassandraReplica(KEYSPACE, ARTISTS)
// Join with "artists" table, selecting only "name" and "country" columns
.joinWithCassandraTable[(String,String)](KEYSPACE, ARTISTS, SomeColumns("name","country"))
.on(SomeColumns("name"))
42
@doanduyhai
Joins pipeline with data locality
LOCAL READ
FROM CASSANDRA
43
@doanduyhai
Joins pipeline with data locality
REPARTITION TO MAP
CASSANDRA REPLICA
44
@doanduyhai
Joins pipeline with data locality
JOIN WITH
DATA LOCALITY
45
@doanduyhai
Perfect data locality scenario
•  read localy from Cassandra
•  use operations that do not require shuffle in Spark (map, filter, …)
•  repartitionbyCassandraReplica()
•  à to a table having same partition key as original table
•  save back into this Cassandra table
Sanitize, validate, normalize, transform data
USE CASE
46
Spark/Cassandra use-case demos
Data cleaning
Schema migration
Analytics
@doanduyhai
Use Cases
Load data from various
sources
Analytics (join, aggregate, transform, …)
Sanitize, validate, normalize, transform data
Schema migration,
Data conversion
48
@doanduyhai
Data cleaning use-cases
Bug in your application ?
Dirty input data ?
☞ Spark job to clean it up! (perfect data locality)
Sanitize, validate, normalize, transform data
49
@doanduyhai
Data Cleaning
https://github.com/doanduyhai/incubator-zeppelin/tree/ApacheBigData
@doanduyhai
Schema migration use-cases
Business requirements change with time ?
Current data model no longer relevant ?
☞ Spark job to migrate data !
Schema migration,
Data conversion
51
@doanduyhai
Data Migration
https://github.com/doanduyhai/incubator-zeppelin/tree/ApacheBigData
@doanduyhai
Analytics use-cases
Given existing tables of performers and albums, I want to :
•  count the number of albums releases by decade (70’s, 80’s, 90’s, …)
☞ Spark job to compute analytics !
Analytics (join, aggregate, transform, …)
53
@doanduyhai
Analytics pipeline
①  Read from production transactional tables
②  Perform aggregation with Spark
③  Save back data into dedicated tables for fast visualization
④  Repeat step ①
54
@doanduyhai
Analytics
https://github.com/doanduyhai/incubator-zeppelin/tree/ApacheBigData
@doanduyhai
Thank You
@doanduyhai
duy_hai.doan@datastax.com
https://academy.datastax.com/

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