Netflix Recommendations Using Spark + Cassandra (Prasanna Padmanabhan & Roopa Tangirala, Netflix) |...
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Netflix Recommendations using Spark + Cassandra Prasanna Padmanabhan Roopa Tangirala
Transcript of Netflix Recommendations Using Spark + Cassandra (Prasanna Padmanabhan & Roopa Tangirala, Netflix) |...
Netflix Recommendations using Spark + Cassandra
Prasanna PadmanabhanRoopa Tangirala
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Turn on Netflix and the absolute best content for you would automatically start playing
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Netflix Recommendations
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Netflix Recommendations
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Ranking
Everything is a RecommendationRo
ws
Over 80% of what members watch comes from our recommendations
Recommendations are driven by Machine Learning Algorithms
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Data Driven
Offline Experiment using Historical
Data
Online A/B Testing
Rollout Feature to ALL members
Success Success
Fail
Algorithmic Page Generation
Trending Now
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Offline Experimentation
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Algorithmic Page Generation
Personalizing the ordering of rows on the homepage
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Algorithmic Page Generation
Without Algorithmic Page Generation With Algorithmic Page Generation
Diversity of the Page
Affinity for specific rows
Drawbacks
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Algorithmic Page Generation
Production
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Algorithmic Page Generation
Production Variant 1
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Algorithmic Page Generation
Production Variant 1 Variant 2
Row DistributionTV/Movie Ratio
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Algorithmic Page Generation
Production Variant 1 Variant 2
Evaluate best variant based on the plays
Actual Plays:
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Algorithmic Page Generation
Production Variant 1 Variant 2
Evaluate best variant based on the plays
Actual Plays:
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Algorithmic Page Generation
Production Variant 1 Variant 2
Evaluate best variant based on the plays
Actual Plays:
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Variant 2
Algorithmic Page Generation
Production Variant 1
Evaluate best variant based on the plays
Actual Plays:
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Offline Experiment ArchitectureMemberSelection
Runs once a day
Ratings Service
S3
Snapshot Snapshot Store
Snapshot Forklift
Viewing History Service
MyList Service
Data Snapshots
Evaluate Metrics
Generate Pages
… …
A/B Test
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Data Model - Requirements
• Need for historical service data
• Optimize for Batch Writes and Point Reads
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Data Model
20161009_1001
20161009_1002
DATE_MEMBER_ID
MyList
BLOB
MyList
BLOB
ROWS
COLUMN
COLUMN FAMILY: MYLIST
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Data Model
20161009_1001
20161009_1002
DATE_MEMBER_ID
ViewingData
BLOB
ViewingData
BLOB
ROWS
COLUMN
COLUMN FAMILY: VIEWING-HISTORY
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Data Model
20161009_1001_0
20161009_1001_1
DATE_MEMBERID_IDX
ViewingData
BLOB
ViewingData
BLOB
ROWS
COLUMN
20161009_1001_2ViewingData
BLOB
COLUMN FAMILY: VIEWING-HISTORY
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Online A/B Testing
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Trending Now
Videos that are Trending and Personalized for you
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Trending Now
It’s 7 PM on a Monday
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Trending Now
It’s 10 PM on a Saturday
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Trending Now
Pokeman
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Fast Feedback LoopUI
Data Systems
Streaming Apps
Rec Systems
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Trending Now - Data InfrastructureImpression
Service
Viewing History Service
UI
Online Services
Trends Store
Compute Trends
Model Training
Captures videos shown in view port
Captures videos played by members
Publish Models
Viewing History Service
Ratings. .. .
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State Management in Cassandra
Video Number of Plays
Stranger Things 100
Narcos 200
Orange is the new Black 300
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State Management in Cassandra
Trends Store
State Present
?Compute Trends
Yes
NoInit State from
Cassandra
Load State
Update State
Read Events
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Data Model - Requirements
• Trending data is for a specific interval of time
• Optimize for Batch Writes and Batch Reads
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Data Model
101_METADATA
102_METADATA
VIDEOID_METADATA
Plays
BLOB
Plays
BLOB
ROWS
COLUMNS
103_METADATAPlays
BLOB
COLUMN FAMILY: Interval 1,Interval 2…Interval N
Impressions
BLOB
Impressions
BLOB
Impressions
BLOB
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Roopa TangiralaEngineering Manager @ NetflixTwitter - @roopatangirala
FORKLIFTER
ARCHITECTURE
SOURCE TARGET
USE CASES
APACHE THRIFT CQL
DEMO
WHY NOT DSE SPARK?
SCALABILITY
COST EFFECTIVENESS
LESSONS LEARNT
TTL HANDLING• TTL Reading And Writing is Asymmetric -
CASSANDRA 12216 • Thrift Column TTL vs CQL Row TTL
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6
5
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2
PARTITION DIFFERENCES
1000
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600000
500000
4000
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300000
200000100k
75k
50k
25k
425k450k475k
400k
325k
350k375k
300k
275k
250k
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200k175k150k125k
500k
525k
550k575k
600k
TUNING• spark.cassandra.connection.keep_aliv
e_ms• spark.cassandra.connection.timeout_
ms• spark.driver.maxResultSize
OOM EXCEPTIONS Spark.executor.memory
spark.cassandra.input.split.size_in_mb
WRITES SPEED SPARK• cassandra.output.batch.size.bytes• cassandra.output.batch.size.rows• cassandra.output.concurrent.writes• cassandra.output.throughput_mb_per_s
ec
Write Timeoutscassandra.output.throughput_mb_per_sec
QUESTIONS?
