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Cassandra for Barcodes, Products and Scans:

The Backend Infrastructure at Scandit

Christof Roduner
Co-founder and COO
christof@scandit.com Link: NoSQL concept and data model

@scandit
www.scandit.com February 1, 2012

AGENDA
2

? About Scandit

? Requirements

? Apache Cassandra

? Scandit backend

WHAT IS SCANDIT?
3

Scandit provides developers best-in-class tools to
build, analyze and monetize product-centric apps.

IDENTIFY ANALYZE MONETIZE
Products User Interest Apps

ANALYZE:
THE SCANALYTICS PLATFORM
4

? Tool for app publishers
? App-specific usage statistics

? Insights into consumer behavior:
? What do users scan?
? Product categories? Groceries, electronics, books, cosmetics, ��?
? Where do users scan?
? At home? Or while in a retail store?
? Top products and brands

? Identify new opportunities:
? Customer engagement
? Product interest
? Cross-selling and up-selling

BACKEND REQUIREMENTS
5

? Product database
? Many millions of products
? Many different data sources
? Curation of product data (filtering, etc.)

? Analysis of scans
? Accept and store high volumes of scans
? Generate statistics over extended time periods
? Correlate with product data

? Provide reports to developers

BACKEND DESIGN GOALS
6

? Scalability
? High-volume storage
? High-volume throughput
? Support large number of concurrent client requests (app)

? Availability

? Low maintenance

WHICH DATABASE?
7

Apache Cassandra
? Large, distributed key-value store (DHT)

? ?NoSQL? Polyglot Persistence

? Inspired by:

? Amazon��s Dynamo distributed storage system
? Google��s BigTable data model
? Originally developed at Facebook
? Inbox search

WHY DID WE CHOOSE IT?
8

? Looked very fast
? Even when data is much larger than RAM

? Performs well in write-heavy environment

? Proven scalability
? Without downtime

? Tunable replication

? Easy to run and maintain
? No sharding
? All nodes are the same - no coordinators, masters, slaves, ��

? Data model
? YMMV��

WHAT YOU HAVE TO GIVE UP
9

? Joins
? Referential integrity
? Transactions
? Expressive query language
? Consistency (tunable, but��)

? Limited support for:
? Schema
? Secondary indices

CASSANDRA DATA MODEL
10

Disclaimer: I tend to say ?hash?
when I mean ?dictionary, map,
? Column families associative array? (Can you tell
my favorite language?)
? Rows
? Columns

? (Supercolumns)
? We��ll skip them - Cassandra developers don��t like
them

COLUMNS AND ROWS
11

? Column:
? Is a name-value pair
? row_key, CF, column, timestamp and value

? Row:
? Has exactly one key
? Contains any number of columns
? Columns are always automatically sorted by their name

? Column family:
? A collection of any number of rows (!)
? Has a name
? ?Like a table?

EXAMPLE COLUMN FAMILY
12

"users": {
Row with key ?christof?
"christof": {
"email": "christof@scandit.com",
"phone": "123-456-7890"
}

"moritz": {
"email": "moritz@scandit.com",
Two columns, automatically
"web": "www.example.com" sorted by their names
} (?email?, ?web?)
}

? A column family ?users? containing two rows
? Columns can be different in every row
? First row has a column named ?phone?, second row does not
? Rows can have many columns
? You can add millions of them

DATA IN COLUMN NAMES
13

? Column names can be used to store data
? Frequent pattern in Cassandra
? Takes advantage of column sorting
"logins": {

"christof": {
"2012-01-29 16:22:30 +0100": "208.115.113.86",
"2012-01-30 07:48:03 +0100": "66.249.66.183",
"2012-01-30 18:06:55 +0100": "208.115.111.70",
"2012-01-31 12:37:26 +0100": "66.249.66.183"
}

"moritz": {
"2012-01-23 01:12:49 +0100": "205.209.190.116"
}

}

SCHEMA AND DATA TYPES
14

? Schema is optional
? Data type can be defined for:
? Keys
? The values of all columns with a given name
? The column names in a CF
? By default, data type BLOB is used

? Data Types
? BLOB (default) ? UUID
? ASCII text ? Integer (arbitrary length)
? UTF8 text ? Float
? Timestamp ? Double
? Boolean ? Decimal

CLUSTER ORGANIZATION
15

Range 1-64,
Node 1 stored on node 2
Token 0

Node 4 Node 2
Token 192 Token 64

Node 3 Range 65-128,
Token 128 stored on node 3

STORING A ROW
16
Range 1-64,
1. Calculate md5 hash for row key stored on node 2
Example: md5(��foobar") = 48
Node 1
Token 0
2. Determine data range for hash
Example: 48 lies within range 1-64

3. Store row on node responsible
Node 4 Node 2
for range
Token 192 Token 64
Example: store on node 2

Node 3
Token 128
Range 65-128,
stored on node 3

IMPLICATIONS
17

? Cluster automatically balanced
? Load is shared equally between nodes
? No hotspots

? Scaling out?
? Easy
? Divide data ranges by adding more nodes
? Cluster rebalances itself automatically

? Range queries not possible
? You can��t retrieve ?all rows from A-C?
? Rows are not stored in their ?natural? order
? Rows are stored in order of their md5 hashes

IF YOU NEED RANGE QUERIES��
18

Option 1: ?Order Preserving Partitioner? (OPP)
? OPP determines node based on a row��s key instead of its hash
? Don��t use it��
? Manually balancing a cluster is hard
? Hotspots
? Balancing cluster for one column family creates hotspot for another

Option 2: Use columns instead of rows
? Columns are always sorted
? Rows can store millions of columns

REPLICATION
19

Replica 1
? Tunable replication factor of row
(RF) Node 1 ?foobar?
Token 0
? RF > 1: rows are automatically
replicated to next RF-1 nodes

? Tunable replication strategy Node 2
Node 4
? ?Ensure two replicas in Token 64
different data centers, racks, Token 192
etc.?

Node 3
Token 128 Replica 2
of row
?foobar?

CLIENT ACCESS
20

? Clients can send read and write
requests to any node
? This node will act as
coordinator
Node 1 Replica 1
? Coordinator forwards request Token 0 of row
to nodes where data resides ?foobar?

Client Node 4 Node 2
Token 192 Token 64

Request:
Replica 2
insert( Node 3 of row
"foobar": { "email": "fb@example.com" } Token 128 ?foobar?
)

CONSISTENCY LEVELS
21

? For all requests, clients can set a consistency level (CL)

? For writes:
? CL defines how many replicas must be written before
?success? is returned to client

? For reads:
? CL defines how many replicas must respond before result is
returned to client

? Consistency levels:
? ONE
? QUORUM
? ALL
? �� (data center-aware levels)

INCONSISTENT DATA
22

? Example scenario:
? Replication factor 2
? Two existing replica for row ?foobar?
? Client overwrites existing columns in ?foobar?
? Replica 2 is down

? What happens:
? Column is updated in replica 1, but not replica 2 (even with CL=ALL !)

? Timestamps to the rescue
? Every column has a timestamp
? Timestamps are supplied by clients
? Upon read, column with latest timestamp wins

? ��Use NTP

PREVENTING INCONSISTENCIES
23

? Read repair

? Hinted handoff

? Anti entropy

RETRIEVING DATA (API)
24
? At a row level, you can��
? Get all rows
? Get a single row by specifying its key
? Get a number of rows by specifying their keys
? Get a range of rows
? Only with OPP, strongly discouraged

? At a column level, you can��
? Get all columns
? Get a single column by specifying its name
? Get a number of columns by specifying their names
? Get a range of columns by specifying the name of the first and
last column

? Again: no ranges of rows

CASSANDRA QUERY LANGUAGE
(CQL)
25

UPDATE users SET
"email" = "christof@scandit.com",
"phone" = "123-456-7890"
WHERE KEY = "christof";

"users": {

"christof": {
"phone": "123-456-7890"
}

"moritz": {
"web": "www.example.com"
}

}

(CQL)
26

SELECT * FROM users WHERE KEY = "christof";

"users": {

"christof": {
"phone": "123-456-7890"
}

"moritz": {
"web": "www.example.com"
}

}

(CQL)
27

SELECT FIRST 3 "2012-01-30 00:00:00 +0100" ..
"2012-01-31 23:59:59 +0100"
FROM logins
WHERE KEY = "christof";

"logins": {

"christof": {
"2012-01-29 16:22:30 +0100": "208.115.113.86",
"2012-01-30 07:48:03 +0100": "66.249.66.183",
"2012-01-30 18:06:55 +0100": "208.115.111.70",
"2012-01-31 12:37:26 +0100": "66.249.66.183"
"2012-02-09 10:27:28 +0100": "218.315.37.21",
}

"moritz": {
"2012-01-23 01:12:49 +0100": "205.209.190.116"
}

}

SECONDARY INDICES
28

? Secondary indices can be defined for (single) columns

? Secondary indices only support equality predicate (=)
in queries

? Each node maintains index for data it owns
? When indexed column is queried, request must be forwarded
to all nodes
? Sometimes better to manually maintain your own index

PRODUCTION EXPERIENCE
29

? No stability issues

? Very fast

? Language bindings don��t have the same quality
? Out of sync, bugs

? Data model is a mental twist

? Design-time decisions sometimes hard to change

? Rudimentary access control

TRYING OUT CASSANDRA
30

? DataStax website
? Company founded by Cassandra developers
? Provides
? Documentation
? Amazon Machine Image

? Apache website

? Mailing lists

CLUSTER AT SCANDIT
31

? Several nodes in two data centers

? Linux machines

? Identical setup on every node
? Allows for easy failover

NODE ARCHITECTURE
32
from mobile apps and web browsers

Phusion Passenger
mod_passenger

Website & REST API
Ruby on Rails, Rack

to other nodes

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Cassandra 2012 scandit

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