Cassandra 3.0 - JSON at scale - StampedeCon 2015
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This session will explore the new features in Cassandra 3.0, starting with JSON support. Cassandra now allows storing JSON directly to Cassandra rows and vice versa, making it trivial to deploy Cassandra as a component in modern service-oriented architectures. Cassandra 3.0 also delivers other enhancements to developer productivity: user defined functions let developers deploy custom application logic server side with any language conforming to the Java scripting API, including Javascript. Global indexes allow scaling indexed queries linearly with the size of the cluster, a first for open-source NoSQL databases. Finally, we will cover the performance improvements in Cassandra 3.0 as well.
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Cassandra 3.0 - JSON at scale - StampedeCon 2015
- 1. ©2014 DataStax Confidential. Do not distribute without consent. CTO, DataStax Jonathan Ellis Project Chair, Apache Cassandra Cassandra 3.0: JSON at Scale
- 2. How we got here
- 11. SELECT offices.name, MAX(orders.created_at) FROM offices NATURAL JOIN orders GROUP BY offices.name;
- 13. Why today is different
- 14. "glossary": { "title": "example glossary", ! ! "GlossDiv": { "title": "S", ! ! ! "GlossList": { "GlossEntry": { "ID": "SGML", ! ! ! ! ! "SortAs": "SGML", ! ! ! ! ! "GlossTerm": "Standard Generalized Markup Language", ! ! ! ! ! "Acronym": "SGML", ! ! ! ! ! "Abbrev": "ISO 8879:1986", ! ! ! ! ! "GlossDef": { "para": "A meta-markup language, used to create markup languages such as DocBook.", ! ! ! ! ! ! "GlossSeeAlso": ["GML", "XML"] }, ! ! ! ! ! "GlossSee": "markup" } } }
- 15. p1 p1 p1
- 16. p1 p1 p1
- 17. p1 p1 p1
- 19. CQL CREATE TABLE users ( id uuid PRIMARY KEY, name text, state text, birth_date int ); CREATE INDEX ON users(state); SELECT * FROM users WHERE state=‘Texas’ AND birth_date > 1950;
- 20. Collections CREATE TABLE example ( id int PRIMARY KEY, tupleval tuple<int, text>, numbers set<int>, words list<text> ); INSERT INTO example (id, tupleval, numbers, words) VALUES (0, (1, 'foo'), {1, 2, 3, 6}, ['the', 'quick', 'brown', 'fox']);
- 21. User-defined types (UDT) CREATE TYPE address (number int, street text); CREATE TABLE users ( id int PRIMARY KEY, street_address frozen<address> ); INSERT INTO users (id, street_address) VALUES (1, {number: 123, street: 'Cassandra Ave'});
- 22. JSON INSERT INTO example JSON '{"id": 0, "tupleval": [1, "foo"], "numbers": [1, 2, 3, 6], "words": ["the", "quick", "brown", "fox"]}'; INSERT INTO users JSON '{"id": 1, "street_address": {"number": 1, "" "street": "Cassandra Ave"}}';
- 23. Nested CREATE TYPE address ( street text, city text, zip_code int, phones set<text> ); CREATE TABLE users ( id uuid PRIMARY KEY, name text, addresses map<text, frozen<address>> );
- 24. Nested INSERT INTO users JSON '{"id": "0514e410-2a9f-11e5-a2cb-0800200c9a66", "name": "jbellis", "addresses": {"home": {"street": "9920 Cassandra Ave", "city": "Austin", "zip_code": 78700, "phones": ["1238614789"]}}}';
- 25. What about schemaless documents?
- 27. {"userid": "2452347", "name": "jbellis", ... } {"userid": 2452348, "name": "jhaddad", ... } {"user_id": 2452349, "name": "jlacefield", ... }
- 31. Performance and scale read-mostly balanced
- 32. Performance and scale read-mostly balanced write-mostly
- 33. Performance and scale read-mostly balanced write-mostly op/analytic
- 35. See also •The myth of schema-less: http://rustyrazorblade.com/2014/07/the-myth-of-schema-less/ •Schema-less is (usually) a lie: https://www.compose.io/articles/schema-less-is-usually-a-lie/ •Schemaless databases don’t exist: https://vividcortex.com/blog/2015/02/24/schemaless-databases-dont- exist/
- 38. Lightweight transactions INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ba27e03fd9...', '2011-06-20 13:50:00') IF NOT EXISTS;
- 39. Lightweight transactions INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ba27e03fd9...', '2011-06-20 13:50:00') IF NOT EXISTS; INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ea24e13ad9...', '2011-06-20 13:50:01') IF NOT EXISTS;
- 40. Lightweight transactions INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ba27e03fd9...', '2011-06-20 13:50:00') IF NOT EXISTS; [applied] ----------- True INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ea24e13ad9...', '2011-06-20 13:50:01') IF NOT EXISTS;
- 41. Lightweight transactions [applied] | username | created_date | name -----------+----------+----------------+---------------- False | pmcfadin | 2011-06-20 ... | Patrick McFadin INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ba27e03fd9...', '2011-06-20 13:50:00') IF NOT EXISTS; [applied] ----------- True INSERT INTO users (username, name, email, password, created_date) VALUES ('pmcfadin', 'Patrick McFadin', ['patrick@datastax.com'], 'ea24e13ad9...', '2011-06-20 13:50:01') IF NOT EXISTS;
- 42. Static columns CREATE TABLE bills ( user text, balance int static, expense_id int, amount int, description text, paid boolean, PRIMARY KEY (user, expense_id) );
- 43. Static columns + LWT CREATE TABLE bills ( user text, balance int static, expense_id int, amount int, description text, paid boolean, PRIMARY KEY (user, expense_id) ); BEGIN BATCH UPDATE bills SET balance = -116 WHERE user='user1' IF balance = 84; INSERT INTO bills (user, expense_id, amount, description, paid) VALUES ('user1', 2, 200, 'hotel room', false); APPLY BATCH;
- 44. 2.2 and 3.0 Preview
- 46. Role-based authorization CREATE ROLE manager WITH PASSWORD 'foo' LOGIN; GRANT authorize TO manager; GRANT manager TO jbellis;
- 47. Hinted handoff improvements CREATE TABLE system.hints ( target_id uuid, hint_id timeuuid, message_version int, mutation blob, PRIMARY KEY (target_id, hint_id, message_version) ) WITH COMPACT STORAGE AND CLUSTERING ORDER BY (hint_id ASC, message_version ASC)
- 56. SSTable-based hints Hint Commitlog Memtable SSTable Memtable SSTable Tombstone Commitlog Compacted
- 69. User-defined functions CREATE FUNCTION my_sin (input double) RETURNS double LANGUAGE java AS ’ return input == null ? null : Double.valueOf(Math.sin(input.doubleValue())); ’; SELECT key, my_sin(value) FROM my_table WHERE key IN (1, 2, 3); also aggregates http://www.slideshare.net/RobertStupp/user-definedfunctionscassandrasummiteu2014 [robert stupp user defined functions]
- 71. Materialized views CREATE MATERIALIZED VIEW songs_by_album AS SELECT * FROM songs WHERE album IS NOT NULL PRIMARY KEY (album, id); SELECT * FROM songs_by_album WHERE album = ‘Tres Hombres’;
- 72. Indexes CREATE TABLE songs ( id uuid PRIMARY KEY, title text, album text, artist text ); CREATE INDEX songs_by_album on songs(album); insert into songs (id, title, artist, album) values ('a3e64f8f...', 'La Grange', 'ZZ Top', 'Tres Hombres'); insert into songs (id, title, artist, album) values ('8a172618...', 'Waitin for the Bus', 'ZZ Top', 'Tres Hombres'); insert into songs (id, title, artist, album) values ('2b09185b...', 'Outside Woman Blues', 'Back Door Slam', 'Roll Away'); SELECT * FROM songs WHERE album = ‘Tres Hombres’;
- 73. Local indexes client title artist album La Grange ZZ Top Tres Hombre s title artist album Outside... Back Door Slam Roll Away title artist album Waitin... ZZ Top Tres Hombres
- 74. Materialized Views client album id Tres Hombres a3e64f8f Tres Hombres 8a172618 album id Roll Away 2b09185b
- 76. Upcoming releases •2.2: July 20th
- 77. Upcoming releases •2.2: July 20th •3.0: Late September
- 78. Upcoming releases •2.2: July 20th •3.0: Late September •3.1: November
- 79. Upcoming releases •2.2: July 20th •3.0: Late September •3.1: November •3.2: December
- 80. Questions