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AWSプロダクトシリーズ
よくわかるAmazon Redshift in 大阪
2014/02/21 アマゾン データ サービス ジャパン株式会社
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Big Data Platform on AWS
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Redshift
EMR
EC2
Analyze
Glacier
S3
DynamoDB
Store
Import Export
Direct Connect
Collect
Kinesis
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Ease of use Lower costs
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no capital investment
pay as you go
no subscriptions
only pay for what you use
Ease of use Lower costs
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programmable
zero admin easy to configure
integrate with existing tools
Ease of use Lower costs
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Store anything
Object storage
Scalable
99.999999999% durability
Amazon S3
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Real-time processing
High throughput; elastic
Easy to use
S3, Redshift, DynamoDB Integrations Amazon Kinesis
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Hadoop/HDFS clusters
Hive, Impala, MapReduce
Easy to use; fully managed
On-demand and spot pricing
Amazon EMR
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NoSQL Database
Seamless scalability
Zero admin
Single digit millisecond latency
Amazon DynamoDB
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Relational data warehouse
Massively parallel
Petabyte scale
Fully managed
$1,000/TB/Year
Amazon Redshift
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Amazon Redshift Fast, simple, petabyte-scale data warehousing for less than $1,000/TB/Year
Rahul Pathak |Senior Product Manager
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Petabyte scale
Massively parallel
Relational data warehouse
Fully managed; zero admin
Amazon Redshift
a lot faster a lot cheaper a whole lot simpler
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Amazon Redshift Quick Overview
Amazon Redshift 概要のおさらい
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Amazon Redshift architecture
• Leader Node – SQL endpoint
– Stores metadata
– Coordinates query execution
• Compute Nodes – Local, columnar storage
– Execute queries in parallel
– Load, backup, restore via Amazon S3
– Parallel load from Amazon DynamoDB
• Hardware optimized for data processing
• Two hardware platforms – DW1: HDD; scale from 2TB to 1.6PB
– DW2: SSD; scale from 160GB to 256TB
10 GigE
(HPC)
Ingestion Backup Restore
JDBC/ODBC
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Amazon Redshift has security built-in
• SSL to secure data in transit
• Encryption to secure data at rest – AES-256; hardware accelerated
– All blocks on disks and in Amazon S3 encrypted
– HSM Support
• No direct access to compute nodes
• Audit logging & AWS CloudTrail integration
• Amazon VPC support
10 GigE
(HPC)
Ingestion
Backup
Restore
Customer VPC
Internal
VPC
JDBC/ODBC
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Amazon Redshift is easy to use
• Provision in minutes
• Monitor query performance
• Point and click resize
• Built in security
• Automatic backups
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Provision a data warehouse in minutes
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Monitor query performance
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Point and click resize
• Resize while remaining online via AWS
Console or API
• Provision a new cluster in the background
and copy data in parallel from node to
node
• Only charged for source cluster until SQL
endpoint has automatically been switched
over via DNS
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Amazon Redshift continuously backs up your data and
recovers from failures
• Replication within the cluster and backup to Amazon S3 to maintain multiple
copies of data at all times
• Backups to Amazon S3 are continuous, automatic, and incremental
– Designed for eleven nines of durability
• Continuous monitoring and automated recovery from failures of drives and nodes
• Able to restore snapshots to any Availability Zone within a region
• Easily enable backups to a second region for disaster recovery
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Amazon Redshift integrates with multiple data sources
Amazon S3
Amazon EMR
Amazon Redshift
DynamoDB
Amazon RDS
Corporate Datacenter
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New Features That Introduced After re:Invent 2013
re:Invent 2013以降の主なアップデート
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Feature Delivery in 2013
Service Launch (2/14)
PDX (4/2)
Temp Credentials (4/11)
Unload Encrypted Files
DUB (4/25)
NRT (6/5)
JDBC Fetch Size (6/27)
Unload logs (7/5)
4 byte UTF-8 (7/18)
Statement Timeout (7/22)
SHA1 Builtin (7/15)
Timezone, Epoch, Autoformat (7/25)
WLM Timeout/Wildcards (8/1)
CRC32 Builtin, CSV, Restore Progress (8/9)
UTF-8 Substitution (8/29)
JSON, Regex, Cursors (9/10)
Split_part, Audit tables (10/3)
SIN/SYD (10/8)
HSM Support (11/11)
Kinesis EMR/HDFS/SSH copy, Distributed Tables, Audit
Logging/CloudTrail, Concurrency, Resize Perf., Approximate Count
Distinct, SNS Alerts (11/13)
SOC1/2/3 (5/8)
Sharing snapshots (7/18)
Resource Level IAM (8/9)
PCI (8/22) Distributed Tables, Single Node Cursor Support, Maximum Connections to 500
(12/13)
EIP Support for VPC Clusters (12/28)
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Summary of Updates after re:Invent
• Amazon Redshift - New Features Galore (2013/11/11) – Distributed Tables - You now have more control over the distribution of a table's rows across compute
nodes.
– Remote Loading - You can now load data into Redshift from remote hosts across an SSH connection.
– Approximate Count Distinct - You can now use a variant of the COUNT function to approximate the number of matching rows.
– Workload Queue Memory Management - You can now apportion available memory across work queues.
– Key Rotation - You can now direct Redshift to rotate keys for an encrypted cluster.
– HSM Support - You can now direct Redshift to use an on-premises Hardware Security Module (HSM) or AWS CloudHSM to manage the encryption master and cluster encryption keys.
– Database Auditing and Logging - You can log connections and user activity to Amazon S3.
– SNS Notification - Redshift can now issue notifications to an Amazon SNS topic when certain events occur.
• Automated Cross-Region Snapshot Copy for Amazon Redshift (2013/11/14) • Faster & More Cost-Effective SSD-Based Nodes for Amazon Redshift(2014/01/24) • AWS CloudFormation Adds Support for Redshift and More (2014/02/10)
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Amazon Redshift Node Types
• Optimized for I/O intensive workloads
• High disk density
• On demand at $0.85/hour
• As low as $1,000/TB/Year
• Scale from 2TB to 1.6PB
DW1.XL: 16 GB RAM, 2 Cores 3 Spindles, 2 TB compressed storage
DW1.8XL: 128 GB RAM, 16 Cores, 24 Spindles 16 TB compressed, 2 GB/sec scan
rate
• High performance at smaller storage size
• High compute and memory density
• On demand at $0.25/hour
• As low as $5,500/TB/Year
• Scale from 160GB to 256TB
DW2.L *New*: 16 GB RAM, 2 Cores, 160 GB compressed SSD storage
DW2.8XL *New*: 256 GB RAM, 32 Cores, 2.56 TB of compressed SSD storage
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Amazon Redshift is priced to let you analyze all your data
DW1 (HDD) Price Per Hour for
DW1.XL Single Node
Effective Annual
Price per TB
On-Demand $ 1.250 $ 5,475
1 Year Reservation $ 0.750 $ 3,283
3 Year Reservation $ 0.452 $ 1,981
DW2 (SSD) Price Per Hour for
DW2.L Single Node
Effective Annual
Price per TB
On-Demand $ 0.330 $ 18,068
1 Year Reservation $ 0.211 $ 11,570
3 Year Reservation $ 0.130 $ 7,127
• Number of nodes x cost per
hour
• No charge for leader node
• No upfront costs
• Pay as you go
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Security, visibility and control
• Audit logging
• SNS Alerts
Redshift
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Visibility and control
• Audit logging
• SNS Alerts
Amazon S3
Amazon Redshift
Database Activity
Logins, Login failures,
Queries, Loads
System Activity
Creates, Changes,
Deletes, Resizes
AWS
CloudTrail
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Visibility and control
• Audit logging
• SNS Alerts
Amazon
Redshift SNS
Topic
Monitoring
Security
Maintenance
Errors
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Batch operations
• Cluster Creation
• Faster Resize
Amazon
Redshift
Amazon S3
Amazon
EMR
Amazon
EC2
Corporate
Data Center
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Batch operations
• Cluster Creation
• Faster Resize
Amazon
Redshift
Amazon S3
Amazon
EMR
Amazon
EC2
Corporate
Data Center
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Batch operations
• Cluster Creation
• Faster Resize
15-20 min
3 min
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Batch operations
• Cluster Creation
• Faster Resize
29 hours
7 hours
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Performance & Concurrency
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Performance & Concurrency
692.8s
34.9s
< 2%
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Performance & Concurrency
5,951.7s
2,151.9s
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Performance & Concurrency
15
50
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How Customers Leverage Amazon Redshift
Amazon Redshift 活用事例
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Common Customer Use Cases
• Reduce costs by extending DW rather than adding HW
• Migrate completely from existing DW systems
• Respond faster to
business; provision in minutes
• Improve performance by an order of magnitude
• Make more data available for analysis
• Access business data via standard reporting tools
• Add analytic functionality to applications
• Scale DW capacity as demand grows
• Reduce HW & SW costs by an order of magnitude
Traditional Enterprise DW Companies with Big Data SaaS Companies
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Amazon Redshift Customers
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Japanese Redshift Customer – ALBERT
• Business Challenge
– Given their data volumes, RDBMS tuning and archiving was causing them a lot of
operational pain and costing them money
• Why AWS?
– Amazon Redshift’s performance and ability to handle large data sets allowed them to
make it the core engine of their analytics, enabling them to provide a private DMP (Data Management Platform) for their customers on the Cloud
– PostgreSQL is their primary RDBMS, and connectivity by PostgreSQL drivers is big technical advantage to choose Redshift.
• Benefits for their business
– Ability to start small and scale as needed
– Scalability and flexibility dramatically lowered the cost of ownership
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Japanese Redshift Customer – Sansan
• Business Challenge – Since “Eight” is business card management solution for consumers, they
needed infrastructure that could start small and scale as needed
• Why AWS? – When they tried out AWS first, they were surprised with the ease of use. AWS
functionality and elasticity were critical factors
• Benefits for their business – Lower costs substantially using reserved instances
– Automation is a key to reduce operational and administration costs. They utilize services such as Amazon SES and Amazon SWF.
– They use Redshift for KPI analytics of their services.
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Growing ecosystem
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Multiple Data Loading Options
• Parallel upload to Amazon S3
• AWS Direct Connect
• AWS Import/Export
• ETL Software
• Systems integrators
Data Integration
Systems Integrators
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Customers on Performance
“Redshift is twenty times faster than Hive” (5x – 20x reduction in query times) link
“Queries that used to take hours came back in seconds. Our analysts are orders of magnitude
more productive.” (20x – 40x reduction in query times) link
…[Redshift] performance has blown away everyone here (we generally see 50-100x speedup
over Hive). link
“Did I mention it's ridiculously fast? We'll be using it immediately to provide our analysts
an alternative to Hadoop.”
“We saw…2x improvement in query times and a 50% reduction in costs”
We regularly process multibillion row datasets and we do that in a matter of hours. link
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Customers on Cost
“[Amazon Redshift] took an industry famous for its opaque pricing, high TCO and unreliable
results and completely turned it on its head.” link
“[Redshift] cost saving is even more impressive…Our analysts like [Redshift] so much they
don’t want to go back.” (4x reduction in cost over HIVE) link
“We saw 50% reduction in costs”
“[Redshift] has reduced our storage and processing costs significantly, helping us to realize
another 60-70 percent savings.” link
“We found that Amazon Redshift offers the performance we needed while freeing us from
the licensing costs of our previous solution” link
“Not only did we avoid 3 months of development work [we] saved approximately $80,000 in
labor…Competitive Advantage realized with just a few clicks.”
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Customer on Ease of Use
“We can spin up an Amazon Redshift cluster, take a snapshot, and scale servers in minutes
instead of days.” link
“With Amazon Redshift and Tableau, anyone in the company can set up any queries they
like…It’s very flexible.” link
“Customers can get consistent, accurate, and useful data fast - in weeks not months or years.”
link
“Compared to Hadoop [Redshift] is much easier for analysts to use. What may have been a
Hadoop project can become just a query in Redshift.” link
“Amazon Redshift is simple to use and reliable. With one click, we can rapidly scale up or down
in real time in alignment with business requirements.” link
“…our team was able to provision Redshift in a matter hours vs. weeks with on-premises
servers.”
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AWS Marketplace
• Find software to use with Amazon
Redshift
• One-click deployments
• Flexible pricing options
http://aws.amazon.com/marketplace
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Questions?
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APPENDIX
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Resources
• Detail Pages
– http://aws.amazon.com/redshift
– https://aws.amazon.com/marketplace/redshift/
• New Features – http://docs.aws.amazon.com/redshift/latest/dg/doc-history.html
– http://docs.aws.amazon.com/redshift/latest/mgmt/document-history.html
• Best Practices
– http://docs.aws.amazon.com/redshift/latest/dg/c_loading-data-best-practices.html
– http://docs.aws.amazon.com/redshift/latest/dg/c_designing-tables-best-practices.html
– http://docs.aws.amazon.com/redshift/latest/dg/c-optimizing-query-performance.html
• Presentations & Webinars: – http://www.youtube.com/watch?v=JxLpj_TnisM (2013 SF Summit Presentation)
– http://www.youtube.com/watch?v=R1m-fwzXMow (Best Practices 1 of 2)
– http://www.youtube.com/watch?v=7ySzRTOyK6o (Best Practices 2 of 2)
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Amazon Redshift dramatically reduces I/O
• Column storage
• Data compression
• Zone maps
• Direct-attached storage
• With row storage you do
unnecessary I/O
• To get total amount, you have to
read everything
ID Age State Amount
123 20 CA 500
345 25 WA 250
678 40 FL 125
957 37 WA 375
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• With column storage, you only
read the data you need
ID Age State Amount
123 20 CA 500
345 25 WA 250
678 40 FL 125
957 37 WA 375
Amazon Redshift dramatically reduces I/O
• Column storage
• Data compression
• Zone maps
• Direct-attached storage
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analyze compression listing;
Table | Column | Encoding
---------+----------------+----------
listing | listid | delta
listing | sellerid | delta32k
listing | eventid | delta32k
listing | dateid | bytedict
listing | numtickets | bytedict
listing | priceperticket | delta32k
listing | totalprice | mostly32
listing | listtime | raw
Slides not intended for redistribution.
Amazon Redshift dramatically reduces I/O
• Column storage
• Data compression
• Zone maps
• Direct-attached storage
• COPY compresses automatically
• You can analyze and override
• More performance, less cost
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Amazon Redshift dramatically reduces I/O
• Column storage
• Data compression
• Zone maps
• Direct-attached storage
10 | 13 | 14 | 26 |…
… | 100 | 245 | 324
375 | 393 | 417…
… 512 | 549 | 623
637 | 712 | 809 …
… | 834 | 921 | 959
10
324
375
623
637
959
• Track the minimum and maximum
value for each block
• Skip over blocks that don’t contain
relevant data
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Amazon Redshift dramatically reduces I/O
• Column storage
• Data compression
• Zone maps
• Direct-attached storage
• Use local storage for performance
• Maximize scan rates
• Automatic replication and
continuous backup
• HDD & SSD platforms
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Amazon Redshift parallelizes and distributes everything
• Query
• Load
• Backup/Restore
• Resize
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• Load in parallel from Amazon S3 or
Amazon DynamoDB or any SSH
connection
• Data automatically distributed and
sorted according to DDL
• Scales linearly with number of nodes
Amazon Redshift parallelizes and distributes everything
• Query
• Load
• Backup/Restore
• Resize
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• Backups to Amazon S3 are automatic, continuous
and incremental
• Configurable system snapshot retention period. Take
user snapshots on-demand
• Cross region backups for disaster recovery
• Streaming restores enable you to resume querying
faster
Amazon Redshift parallelizes and distributes everything
• Query
• Load
• Backup/Restore
• Resize
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• Resize while remaining online
• Provision a new cluster in the background
• Copy data in parallel from node to node
• Only charged for source cluster
Amazon Redshift parallelizes and distributes everything
• Query
• Load
• Backup/Restore
• Resize
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• Automatic SQL endpoint switchover
via DNS
• Decommission the source cluster
• Simple operation via Console or API
Amazon Redshift parallelizes and distributes everything
• Query
• Load
• Backup/Restore
• Resize