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C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
C* Summit 2013: The World's Next Top Data Model by Patrick McFadin
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C* Summit 2013: The World's Next Top Data Model by Patrick McFadin

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You know you need Cassandra for it's uptime and scaling, but what about that data model? Let's bridge that gap and get you building your game changing app. We'll break down topics like storing objects …

You know you need Cassandra for it's uptime and scaling, but what about that data model? Let's bridge that gap and get you building your game changing app. We'll break down topics like storing objects and indexing for fast retrieval. You will see by understanding a few things about Cassandra internals, you can put your data model in the spotlight. The goal of this talk is to get you comfortable working with data in Cassandra throughout the application lifecycle. What are you waiting for? The cameras are waiting!

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  • 1. #CASSANDRA13Patrick McFadin | Solution Architect, DataStaxThe Worlds Next Top Data Model
  • 2. #CASSANDRA13The saga continues!★ Data model is dead, long live thedata model.★ Bridging from Relational to Cassandra★ Become a SuperModeler★ Core data modeling techniquesusing CQL
  • 3. #CASSANDRA13Because I love talking about thisJust to recap...
  • 4. #CASSANDRA13Why 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...
  • 5. #CASSANDRA13When 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
  • 6. #CASSANDRA13You get the datamodel right!
  • 7. #CASSANDRA13So 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
  • 8. #CASSANDRA13But wait you sayCQL doesn’t do dynamic wide rows!
  • 9. #CASSANDRA13Yes it can!* CQL does wide rows the same way you did them in Thrift* No really* Read this blog posthttp://www.datastax.com/dev/blog/does-cql-support-dynamic-columns-wide-rows...or just trust me and I’ll show you how
  • 10. #CASSANDRA13Customers giving you money is a good reason for uptimeShopping Cart Data Model
  • 11. #CASSANDRA13Shopping 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
  • 12. #CASSANDRA13Shopping cart datamodel* Each customer can haveone or more shoppingcarts* De-normalize data forfast access* Shopping cart == Onepartition (Row LevelIsolation)* Each item a new column
  • 13. #CASSANDRA13Shopping cart datamodelCREATE 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,Garmin910XT,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 FootPod,Bluetooth Smart foot pod,64.00{Related:Timex foot pod,Volume Discount:25});One partition (storage row) of dataItem details. Flexible for whatevPartition row key for one users cartCreates partition row key
  • 14. #CASSANDRA13Watching users, making decisions. Freaky, but cool.User Activity Tracking
  • 15. #CASSANDRA13User 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 longThe bad
  • 16. #CASSANDRA13User activity data model* Interaction points storedper user in short table* Long term interactionstored in similar table withdate partition* Process long term laterusing batch* Reverse time series to getlast N items
  • 17. #CASSANDRA13User activity data modelCREATE 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,Normallogin)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 timestampExpire after 30 days
  • 18. #CASSANDRA13Data model usageusername | interaction_time | detail | activity_code----------+--------------------------------------+------------------------------------------+------------------pmcfadin | 9ccc9df0-d076-11e2-923e-5d8390e664ec | Entered shopping area: Jewelry | 301pmcfadin | 9c652990-d076-11e2-923e-5d8390e664ec | Created shopping cart: Anniversary gifts | 202pmcfadin | 1b5cef90-d076-11e2-923e-5d8390e664ec | Deleted shopping cart: Gadgets I want | 205pmcfadin | 1b0e5a60-d076-11e2-923e-5d8390e664ec | Opened shopping cart: Gadgets I want | 201pmcfadin | 1b0be960-d076-11e2-923e-5d8390e664ec | Normal login | 100select * from user_activity limit 5;Maybe put a sale item for flowers too?
  • 19. #CASSANDRA13Machines generate logs at a furious pace. Be ready.Log collection/aggregation
  • 20. #CASSANDRA13Log 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 costprohibitive* Batch analysis of logs too late for some usecasesThe bad
  • 21. #CASSANDRA13Log collection datamodel* Use Flume to collect and fanout data to various tables* Tables for lookup based onsource and time* Tables for dashboard withaggregation and summation
  • 22. #CASSANDRA13Log collection datamodelCREATE 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
  • 23. #CASSANDRA13Log dashboard025507510010:01 10:03 10:05 10:07 10:09 10:11 10:13 10:15 10:17 10:19Sucessful LoginsFailed LoginsSELECT date_to_minute,successful_loginsFROM login_successLIMIT 20;SELECT date_to_minute,failed_loginsFROM login_failureLIMIT 20;
  • 24. #CASSANDRA13Because mistaks mistakes happenUser Form Versioning
  • 25. #CASSANDRA13Form versioning usecase* Store every possible version efficiently* Scale to any number of users* Commit/Rollback functionality on a form* In RDBMS, many relations that need complicatedjoin* Needs to be in cloud and local data centerThe bad
  • 26. #CASSANDRA13Form version data model* Each user has a form* Each form needs versioning* Separate table to store liveversion* Exclusive lock on a form
  • 27. #CASSANDRA13Form version data modelCREATE 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_versionSET locked_by = pmcfadinWHERE username = pmcfadinAND form_id = 1138AND 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 version2. Lock for one user3. Insert new version. Release lock
  • 28. #CASSANDRA13That’s it!“Mind what you have learned. Save you it can.”- Yoda. Master Data Modeler
  • 29. #CASSANDRA13Your 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

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