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![@chbatey
Hello JSON
• create TABLE user (username text primary key,
first_name text , last_name text , emails set<text> ,
country text);
• INSERT INTO user JSON '{"username": "chbatey",
"first_name":"Christopher", "last_name": "Batey",
“emails":["christopher.batey@datastax.com"]}';](https://image.slidesharecdn.com/2-dundee-cassandra3-150710123449-lva1-app6891/75/2-Dundee-Cassandra-3-5-2048.jpg)
![@chbatey
Cassandra HTTP Wrapper?
@RequestMapping(method = {RequestMethod.POST}, value = "/{keyspace}/{table}", consumes = "application/json")
public ResponseEntity<String> store(@PathVariable String keyspace, @PathVariable String table, @RequestBody String body) {
session.execute(String.format("insert into %s.%s JSON '%s'", keyspace, table, body));
return ResponseEntity.ok("OK");
}
Keyspace
Table
Raw JSON
curl --header "Content-Type: application/json" -X POST -v "localhost:8080/twotwo/
user" --data '{"username": "trev2", "country": null, "emails": ["trevor@gmail.com",
"trevor@yahoo.com"], "first_name": "trevor", "last_name": "bunting", "movies":
null}'](https://image.slidesharecdn.com/2-dundee-cassandra3-150710123449-lva1-app6891/75/2-Dundee-Cassandra-3-9-2048.jpg)
Uploaded byChristopher Batey
2 Dundee - Cassandra-3
Cassandra 2.2 and 3.0 introduced several new features including support for JSON, user defined functions and aggregates, role-based authentication, and a new storage engine. Cassandra 3.0 also introduced materialized views, which allow data to be pre-computed and stored for faster queries, reducing the need for applications to manually denormalize data. The document provides examples of using new features like JSON, user defined types and functions, aggregates, and discusses how materialized views can improve performance over secondary indexes by pre-computing and storing duplicate data within Cassandra.
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2 Dundee - Cassandra-3
- 1. ©2013 DataStax Confidential.Do not distribute without consent. @chbatey Christopher Batey Cassandra 2.2 and 3.0
- 2. @chbatey First comes ablog • Each new feature has a vastly more detailed blog post: http://christopher-batey.blogspot.co.uk/
- 3. @chbatey Were did 2.2come from?
- 4. @chbatey New features • 2.2 -JSON - User defined functions - User defined aggregates - Role based authentication - The small print • 3.0 - New storage engine - Materialised views
- 5. @chbatey Hello JSON • createTABLE user (username text primary key, first_name text , last_name text , emails set<text> , country text); • INSERT INTO user JSON '{"username": "chbatey", "first_name":"Christopher", "last_name": "Batey", “emails":["christopher.batey@datastax.com"]}';
- 6.
- 7. @chbatey JSON + UserDefined Types • CREATE TYPE movie (title text, time timestamp, description text); • ALTER TABLE user ADD movies set<frozen<movie>>; • UPDATE user SET movies = { { title:'Batman', time:'2011-02-03T04:05:00+0000', description: 'This film rocks' } } where username = 'chbatey';
- 8.
- 9. @chbatey Cassandra HTTP Wrapper? @RequestMapping(method= {RequestMethod.POST}, value = "/{keyspace}/{table}", consumes = "application/json") public ResponseEntity<String> store(@PathVariable String keyspace, @PathVariable String table, @RequestBody String body) { session.execute(String.format("insert into %s.%s JSON '%s'", keyspace, table, body)); return ResponseEntity.ok("OK"); } Keyspace Table Raw JSON curl --header "Content-Type: application/json" -X POST -v "localhost:8080/twotwo/ user" --data '{"username": "trev2", "country": null, "emails": ["trevor@gmail.com", "trevor@yahoo.com"], "first_name": "trevor", "last_name": "bunting", "movies": null}'
- 10. @chbatey User defined functions •Run code on the server !Dangerous! • Java + JavaScript supported out of the box
- 11. @chbatey UDF example CREATE TABLEuser ( username text primary key, first_name text , last_name text , emails set<text> , country text);
- 12. @chbatey Custom name CREATE FUNCTIONname ( first_name text, last_name text ) CALLED ON NULL INPUT RETURNS text LANGUAGE java AS ‘ return first_name + " " + last_name; ‘; cqlsh:twotwo> select name(first_name, last_name) FROM user; twotwo.name(first_name, last_name) ------------------------------------ Christopher Batey
- 13. @chbatey User defined aggregates CREATEAGGREGATE average ( int ) SFUNC averageState STYPE tuple<int,bigint> FINALFUNC averageFinal INITCOND (0, 0); Called for every row state passed between Initial state Return type (CQL) Optional function called on final state
- 14. @chbatey State function CREATE FUNCTIONaverageState ( state tuple<int,bigint>, value int ) CALLED ON NULL INPUT RETURNS tuple<int,bigint> LANGUAGE java AS ' if (val != null) { state.setInt(0, state.getInt(0)+1); state.setLong(1, state.getLong(1)+val.intValue()); } return state; '; Type Columns
- 15. @chbatey Final function CREATE FUNCTIONaverageFinal ( state tuple<int,bigint> ) CALLED ON NULL INPUT RETURNS double LANGUAGE java AS ' double r = 0; if (state.getInt(0) == 0) return null; double r = state.getLong(1) / state.getInt(0); return Double.valueOf(r); '; Type
- 16. @chbatey Putting it alltogether
- 17. @chbatey Customer events CREATE AGGREGATEcount_by_type(text) SFUNC countEventTypes STYPE map<text, int> INITCOND {}; CREATE FUNCTION countEventTypes( state map<text, int>, type text ) CALLED ON NULL INPUT RETURNS map<text, int> LANGUAGE java AS ' Integer count = (Integer) state.get(type); if (count == null) count = 1; else count = count + 1; state.put(type, count); return state; ' ;
- 18.
- 19. @chbatey Built in aggregates •count • max • min • avg • sum https://github.com/apache/cassandra/blob/trunk/src/java/org/apache/cassandra/cql3/functions/AggregateFcts.java
- 20. @chbatey Built in timefunctions https://github.com/apache/cassandra/blob/trunk/src/java/org/apache/cassandra/cql3/functions/TimeFcts.java
- 21. @chbatey Built in aggregatesin action
- 22.
- 23.
- 24. @chbatey Small print • Newtypes - smallint - short - tinyint - byte - date - time • Warnings now sent back to client - batch too large
- 25.
- 26. @chbatey Materialsed views • Designedto stop *you* having to duplicate • Do we need a secondary index primer?
- 27. @chbatey Customer events table CREATETABLE if NOT EXISTS customer_events ( customer_id text, staff_id text, store_type text, time timeuuid , event_type text, PRIMARY KEY (customer_id, time)) create INDEX on customer_events (staff_id) ;
- 28. @chbatey Indexes to therescue? customer_id time staff_id chbatey 2015-03-03 08:52:45 trevor chbatey 2015-03-03 08:52:54 trevor chbatey 2015-03-03 08:53:11 bill chbatey 2015-03-03 08:53:18 bill rusty 2015-03-03 08:56:57 bill rusty 2015-03-03 08:57:02 bill rusty 2015-03-03 08:57:20 trevor staff_id customer_id trevor chbatey trevor chbatey bill chbatey bill chbatey bill rusty bill rusty trevor rusty
- 29. @chbatey Secondary index arelocal • The staff_id partition in the secondary index is not distributed like a normal table • The secondary index entries are only stored on the node that contains the customer_id partition
- 30. @chbatey Indexes to therescue? staff_id customer_id trevor chbatey trevor chbatey bill chbatey bill chbatey staff_id customer_id bill rusty bill rusty trevor rusty A B chbatey rusty customer_id time staff_id chbatey 2015-03-03 08:52:45 trevor chbatey 2015-03-03 08:52:54 trevor chbatey 2015-03-03 08:53:11 bill chbatey 2015-03-03 08:53:18 bill rusty 2015-03-03 08:56:57 bill rusty 2015-03-03 08:57:02 bill rusty 2015-03-03 08:57:20 trevor customer_events table staff_id customer_id trevor chbatey trevor chbatey bill chbatey bill chbatey bill rusty bill rusty trevor rusty staff_id index
- 31. @chbatey Do it yourself index CREATE TABLE if NOT EXISTS customer_events ( customer_id text, statff_id text, store_type text, time timeuuid , event_type text, PRIMARY KEY (customer_id, time)) CREATE TABLE if NOT EXISTS customer_events_by_staff ( customer_id text, statff_id text, store_type text, time timeuuid , event_type text, PRIMARY KEY (staff_id, time))
- 32.
- 33.
- 34.
- 35. @chbatey KillrWeather data model INSERTINTO raw_weather_data(wsid, year, month, day, hour, country_code, state_code, temperature, one_hour_precip ) values ('station1', 2012, 12, 25, 1, 'GB', 'Cumbria', 14.0, 20) ; INSERT INTO raw_weather_data(wsid, year, month, day, hour, country_code, state_code, temperature, one_hour_precip ) values ('station2', 2012, 12, 25, 1, 'GB', 'Cumbria', 4.0, 2) ; INSERT INTO raw_weather_data(wsid, year, month, day, hour, country_code, state_code, temperature, one_hour_precip ) values ('station3', 2012, 12, 25, 1, 'GB', 'Greater London', 16.0, 10) ;
- 36.
- 37. @chbatey Fine print • Primarykey columns + one other in your MV primary key • Un-used Primary key columns are added to the end of your MV PK • If the part of your primary key is NULL then it won't appear in the materialised view • This is not free!
- 38.
- 39.
- 40. @chbatey Conclusions • We stilldenormalise and duplicate to achieve scalability and performance • We just let C* do it for us :)