This document discusses Strikingly Analytics, an analytics platform built using Amazon Web Services (AWS) technologies like Apache Kylin, Elastic MapReduce, and DynamoDB. It collects and analyzes clickstream data from Strikingly's website. Key points discussed include how it uses Kylin to enable SQL queries on large datasets, runs ETL processes on AWS, and scales elastically using services like ECS, ALB, and Auto-Scaling. The system provides interactive queries with sub-4 millisecond latency while maintaining high availability and scalability.

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Data Platform Engineer @ Strikingly
PMC of Apache Kylin, Software Architect @ Kyligence
Strikingly Analytics
AWS Apache Kylin

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• 2012
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• :
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• 2016
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• 2017
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Strikingly Analytics
• (ClickStream)
• Strikingly/
• (BI)
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•

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Strikingly Analytics
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•
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• ( )
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(AWS) (Hadoop Kylin)

5. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
Amazon Web Services
• Strikingly/
AWS
AWS
• AWS
Google
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•
AWS
• AWS Java SDK
EMR
Jar
• S3 DynamoDB

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Apache Kylin
• Hadoop
EMR
• HBase
• (Job Query )
Rebalance
• SQL
Ad-hoc
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• JDBC RESTful API
• RESTful API

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Strikingly Analytics
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•

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• Application Load
Balancer
•
• Access Log
S3
• 5- 10
• ECS
• Elastic MapReduce
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• Hadoop
• S3
DynamoDB
Java Library
• S3
• Elastic Container
Service
•
•
ALB
• Task

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•
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Application Load Balancer
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•
•
• (10x)

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•
•
• AWS
Java Library
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•
• AWS Jar
ETL
• S3
Elastic Map Reduce

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•
• EMR Hadoop
• Ad-hoc SQL
•
• RESTful API
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Apache Kylin
• ( )
•
•
• Kylin
TODO ( )
Kylin AWS

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• Job
Query
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S3
HBase/HDFS
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Segment

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46. © 2018, Amazon Web Services, Inc. or its affiliates. All rights reserved.
•
• Auto-Scale
• ALB
• EC2
Elastic Container Service

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•
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• P99
4 ms
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ClickStream

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• Kylin
“ ”
• DynamoDB
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• Apache Calcite SQL

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