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The world's next top data model

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#CASSANDRA13
Patrick McFadin | Solution Architect, DataStax
The World's Next Top Data Model
Monday, June 24, 13

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#CASSANDRA13
The saga continues!
★ Data model is dead, long live the data
model.
★ Bridging from Relational to Cassandra
★...

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#CASSANDRA13
Because I love talking about this
Just to recap...
Monday, June 24, 13

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The world's next top data model

  1. 1. #CASSANDRA13 Patrick McFadin | Solution Architect, DataStax The World's Next Top Data Model Monday, June 24, 13
  2. 2. #CASSANDRA13 The saga continues! ★ Data model is dead, long live the data model. ★ Bridging from Relational to Cassandra ★ Become a Super Modeler ★ Core data modeling techniques using CQL Monday, June 24, 13
  3. 3. #CASSANDRA13 Because I love talking about this Just to recap... Monday, June 24, 13
  4. 4. #CASSANDRA13 Why does this matter? * Cassandra lives closer to your users or applications * Not a hammer for all use case nails * Proper use case, proper model... * Get it wrong and... Monday, June 24, 13
  5. 5. #CASSANDRA13 When to use Cassandra* * Need to be in more than one datacenter. active-active * Scaling from 0 to, uh, well... we’re not really sure. * Need as close to 100% uptime as possible. * Getting these from any other solution would just be mega $ and... *nutshell version. These are all ORs not ANDs Monday, June 24, 13
  6. 6. #CASSANDRA13 You get the data model right! Monday, June 24, 13
  7. 7. #CASSANDRA13 So let’s do that * Four real world examples * Use case, what they were avoiding and model to accomplish * You may think this is you, but it isn’t. I hear these all the time. * All examples are in CQL3 Monday, June 24, 13
  8. 8. #CASSANDRA13 But wait you say CQL doesn’t do dynamic wide rows! Monday, June 24, 13
  9. 9. #CASSANDRA13 Yes it can! * CQL does wide rows the same way you did them in Thrift * No really * Read this blog post http://www.datastax.com/dev/blog/does-cql-support-dynamic-columns-wide-rows ...or just trust me and I’ll show you how Monday, June 24, 13
  10. 10. #CASSANDRA13 Customers giving you money is a good reason for uptime Shopping Cart Data Model Monday, June 24, 13
  11. 11. #CASSANDRA13 Shopping cart use case * Store shopping cart data reliably * Minimize (or eliminate) downtime. Multi-dc * Scale for the “Cyber Monday” problem * Every minute off-line is lost $$ * Online shoppers want speed! The bad Monday, June 24, 13
  12. 12. #CASSANDRA13 Shopping cart data model * Each customer can have one or more shopping carts * De-normalize data for fast access * Shopping cart == One partition (Row Level Isolation) * Each item a new column Monday, June 24, 13
  13. 13. #CASSANDRA13 Shopping cart data model CREATE TABLE user ( ! username varchar, ! firstname varchar, ! lastname varchar, ! shopping_carts set<varchar>, ! PRIMARY KEY (username) ); CREATE TABLE shopping_cart ( ! username varchar, ! cart_name text ! item_id int, ! item_name varchar, description varchar, ! price float, ! item_detail map<varchar,varchar> ! PRIMARY KEY ((username,cart_name),item_id) ); INSERT INTO shopping_cart (username,cart_name,item_id,item_name,description,price,item_detail) VALUES ('pmcfadin','Gadgets I want',8675309,'Garmin 910XT','Multisport training watch',349.99, {'Related':'Timex sports watch', 'Volume Discount':'10'}); INSERT INTO shopping_cart (username,cart_name,item_id,item_name,description,price,item_detail) VALUES ('pmcfadin','Gadgets I want',9748575,'Polaris Foot Pod','Bluetooth Smart foot pod',64.00 {'Related':'Timex foot pod', 'Volume Discount':'25'}); One partition (storage row) of data Item details. Flexible for whatev Partition row key for one users cart Creates partition row key Monday, June 24, 13
  14. 14. #CASSANDRA13 Watching users, making decisions. Freaky, but cool. User Activity Tracking Monday, June 24, 13
  15. 15. #CASSANDRA13 User activity use case * React to user input in real time * Support for multiple application pods * Scale for speed * Losing interactions is costly * Waiting for batch(hadoop) is to long The bad Monday, June 24, 13
  16. 16. #CASSANDRA13 User activity data model * Interaction points stored per user in short table * Long term interaction stored in similar table with date partition * Process long term later using batch * Reverse time series to get last N items Monday, June 24, 13
  17. 17. #CASSANDRA13 User activity data model CREATE TABLE user_activity ( ! username varchar, ! interaction_time timeuuid, ! activity_code varchar, ! detail varchar, ! PRIMARY KEY (username, interaction_time) ) WITH CLUSTERING ORDER BY (interaction_time DESC); CREATE TABLE user_activity_history ( ! username varchar, ! interaction_date varchar, ! interaction_time timeuuid, ! activity_code varchar, ! detail varchar, ! PRIMARY KEY ((username,interaction_date),interaction_time) ); INSERT INTO user_activity (username,interaction_time,activity_code,detail) VALUES ('pmcfadin',0D1454E0-D202-11E2-8B8B-0800200C9A66,'100','Normal login') USING TTL 2592000; INSERT INTO user_activity_history (username,interaction_date,interaction_time,activity_code,detail) VALUES ('pmcfadin','20130605',0D1454E0- D202-11E2-8B8B-0800200C9A66,'100','Normal login'); Reverse order based on timestamp Expire after 30 days Monday, June 24, 13
  18. 18. #CASSANDRA13 Data model usage username | interaction_time | detail | activity_code ----------+--------------------------------------+------------------------------------------+------------------ pmcfadin | 9ccc9df0-d076-11e2-923e-5d8390e664ec | Entered shopping area: Jewelry | 301 pmcfadin | 9c652990-d076-11e2-923e-5d8390e664ec | Created shopping cart: Anniversary gifts | 202 pmcfadin | 1b5cef90-d076-11e2-923e-5d8390e664ec | Deleted shopping cart: Gadgets I want | 205 pmcfadin | 1b0e5a60-d076-11e2-923e-5d8390e664ec | Opened shopping cart: Gadgets I want | 201 pmcfadin | 1b0be960-d076-11e2-923e-5d8390e664ec | Normal login | 100 select * from user_activity limit 5; Maybe put a sale item for flowers too? Monday, June 24, 13
  19. 19. #CASSANDRA13 Machines generate logs at a furious pace. Be ready. Log collection/aggregation Monday, June 24, 13
  20. 20. #CASSANDRA13 Log collection use case * Collect log data at high speed * Cassandra near where logs are generated. Multi-datacenter * Dice data for various uses. Dashboard. Lookup. Etc. * The scale needed for RDBMS is cost prohibitive * Batch analysis of logs too late for some use cases The bad Monday, June 24, 13
  21. 21. #CASSANDRA13 Log collection data model * Use Flume to collect and fan out data to various tables * Tables for lookup based on source and time * Tables for dashboard with aggregation and summation Monday, June 24, 13
  22. 22. #CASSANDRA13 Log collection data model CREATE TABLE log_lookup ( ! source varchar, ! date_to_minute varchar, ! timestamp timeuuid, ! raw_log blob, ! PRIMARY KEY ((source,date_to_minute),timestamp) ); CREATE TABLE login_success ( ! source varchar, ! date_to_minute varchar, ! successful_logins counter, ! PRIMARY KEY (source,date_to_minute) ) WITH CLUSTERING ORDER BY (date_to_minute DESC); CREATE TABLE login_failure ( ! source varchar, ! date_to_minute varchar, ! failed_logins counter, ! PRIMARY KEY (source,date_to_minute) ) WITH CLUSTERING ORDER BY (date_to_minute DESC); Consider storing raw logs as GZIP Monday, June 24, 13
  23. 23. #CASSANDRA13 Log dashboard 0 25 50 75 100 10:01 10:03 10:05 10:07 10:09 10:11 10:13 10:15 10:17 10:19 Sucessful Logins Failed Logins SELECT date_to_minute,successful_logins FROM login_success LIMIT 20; SELECT date_to_minute,failed_logins FROM login_failure LIMIT 20; Monday, June 24, 13
  24. 24. #CASSANDRA13 Because mistaks mistakes happen User Form Versioning Monday, June 24, 13
  25. 25. #CASSANDRA13 Form versioning use case * Store every possible version efficiently * Scale to any number of users * Commit/Rollback functionality on a form * In RDBMS, many relations that need complicated join * Needs to be in cloud and local data center The bad Monday, June 24, 13
  26. 26. #CASSANDRA13 Form version data model * Each user has a form * Each form needs versioning * Separate table to store live version * Exclusive lock on a form Monday, June 24, 13
  27. 27. #CASSANDRA13 Form version data model CREATE TABLE working_version ( ! username varchar, ! form_id int, ! version_number int, ! locked_by varchar, ! form_attributes map<varchar,varchar> ! PRIMARY KEY ((username, form_id), version_number) ) WITH CLUSTERING ORDER BY (version_number DESC); INSERT INTO working_version (username, form_id, version_number, locked_by, form_attributes) VALUES ('pmcfadin',1138,1,'', {'FirstName<text>':'First Name: ', 'LastName<text>':'Last Name: ', 'EmailAddress<text>':'Email Address: ', 'Newsletter<radio>':'Y,N'}); UPDATE working_version SET locked_by = 'pmcfadin' WHERE username = 'pmcfadin' AND form_id = 1138 AND version_number = 1; INSERT INTO working_version (username, form_id, version_number, locked_by, form_attributes) VALUES ('pmcfadin',1138,2,null, {'FirstName<text>':'First Name: ', 'LastName<text>':'Last Name: ', 'EmailAddress<text>':'Email Address: ', 'Newsletter<checkbox>':'Y'}); 1. Insert first version 2. Lock for one user 3. Insert new version. Release lock Monday, June 24, 13
  28. 28. #CASSANDRA13 That’s it! “Mind what you have learned. Save you it can.” - Yoda. Master Data Modeler Monday, June 24, 13
  29. 29. #CASSANDRA13 Your data model is next! * Try out a few things * See what works * All else fails, engage an expert in the community * Want more? Follow me on twitter: @PatrickMcFadin Monday, June 24, 13

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