The document outlines an agenda for a workshop on Amazon Redshift conducted on December 6, 2014, covering topics such as the advantages of analytic databases, specific features of Redshift, and hands-on exercises for loading data and performing queries. Participants are guided on the necessary preparations, including AWS account setup and SQL Workbench installation, to effectively use Redshift. The session concludes with instructions on shutting down the database and resources for further learning.

1. Amazon Redshift
Saturday, December 6, 2014

2. Agenda
08:30 AM Breakfast
09:00 AM Introduction and Strengths of Technologies
10:00 AM break + set up query tool
10:20 AM Hadoop hands-on
10:55 AM break
11:10 AM Redshift hands-on
11:40 AM Operationalizing your code
12:00 PM adjourn
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3. Session Goals
• Understand:
• Why an Analytic Database?
• What is Amazon Redshift
• Do:
• ‘Fire Up’ an Redshift Database
• Load Data
• Do a few queries
• Shut it down
• Have fun!
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4. Why an Analytic Database?
Why use one?
• It a database optimized for read-only queries.
• It’s fast
• It can handle a lot of data
Why not to use one?
• Poor Transaction processing (aka OLTP)
• Rollback, multi-phase commits, etc
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5. Under the hood.
Analytic Database typically have features like:
• Compression
• Column (as opposed to row) storage
• Parallel queries across clusters of machines
• Support for partitioning
• Other cool stuff to make your queries fast
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6. Columns vs Row Storage
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7. Parallel Queries
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8. Compression
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9. Amazon Redshift is an Example of
an Analytic Database
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10. Amazon Redshift uses typical SQL
to query the database
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11. Let’s Get Stared!
The basics:
• You will need an AWS account
• AWS Secret Key
• AWS Access Key
• Install SQL Workbench
• http://www.sql-workbench.net/manual/install.html
• Install Postres JDBC Drivers:
• http://jdbc.postgresql.org/
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12. Let’s Get Stared!: https://aws.amazon.com/
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Click Here

13. Redshift: https://console.aws.amazon.com/redshift/.
Click Here
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14. Launch: http://docs.aws.amazon.com/redshift/latest/gsg/rs-gsg-launch-sample-cluster.html
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Fill these out

15. Single Node: https://console.aws.amazon.com/redshift/home?region=us-east-1#launch-cluster:
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Single Node

16. Security: https://console.aws.amazon.com/redshift/home?region=us-east-1#launch-cluster:
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East, not in VPC, default,
no alarms (below)

17. Review: https://console.aws.amazon.com/redshift/home?region=us-east-1#launch-cluster:
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Review

18. Launch!:
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Click

19. Launch!:
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Click

20. Wait:
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Wait, then click

21. When Active:
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You’ll need these details

22. Connect with SQL Workbench:
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Select Connect Window

23. Connect with SQL Workbench:
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Fill this out

24. Get the JDBC URL
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Copy this

25. Connect with SQL Workbench:
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Paste and Fill this out

26. Success!:
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27. New SQL Tab
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Add Tab

28. New SQL Tab
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Add Tab

29. Make Tables
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Create Some Tables
CREATE TABLE rankings
(
pageURL VARCHAR(300),
pageRank INT,
avgDuration INT
);
CREATE TABLE uservisits
(
sourceIP VARCHAR(116),
destinationURL VARCHAR(100),
visitDate DATE,
adRevenue FLOAT,
UserAgent VARCHAR(256),
cCode CHAR(3),
lCode CHAR(6),
searchWord VARCHAR(32),
duration INT
);

30. Load Data
copy uservisits FROM 's3://big-data-benchmark/pavlo/text/tiny/uservisits/' CREDENTIALS
'aws_access_key_id=<your key>;aws_secret_access_key=<your key>' delimiter ',';
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Load Data from S3
copy rankings FROM 's3://big-data-benchmark/pavlo/text/tiny/rankings/' CREDENTIALS
'aws_access_key_id =<your key>;aws_secret_access_key =<your key>' delimiter ',';

31. Load Bigger Data
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Load Data from S3
's3://big-data-benchmark/pavlo/text/tiny/uservisits/‘
-- options: "tiny", "1node", "5nodes", "10nodes"

32. Simple Queries
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Query
select * from uservisits limit 100;
SELECT COUNT(*) from uservisits;
select * from rankings limit 100;
SELECT COUNT(*) from rankings;

33. Complex Queries
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Query
SELECT pageURL, pageRank FROM rankings WHERE pageRank > 10;
SELECT sourceIP, SPLIT_PART(sourceIP, '.', 1) as fn, SPLIT_PART(sourceIP, '.', 2) as sn FROM
uservisits LIMIT 100;
SELECT sourceIP,
SUM(adRevenue) AS totalRevenue,
AVG(pageRank) AS pageRank
FROM rankings R
JOIN (SELECT sourceIP,
destinationURL,
adRevenue
FROM uservisits uv) NUV ON (R.pageURL = NUV.destinationURL)
GROUP BY sourceIP
ORDER BY totalRevenue DESC LIMIT 100;

34. Shut it down!
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Click

35. Shut it down!
Click
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36. Shut it down!
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No snapshot

37. Shut it down!
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38. Thanks … happy querying!
See also
• http://docs.aws.amazon.com/redshift/latest/gsg/getting-started.html
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