![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']);
INSERT INTO example JSON
'{"id": 0,
"tupleval": [1, "foo"],
"numbers": [1, 2, 3, 6],
"words": ["the", "quick", "brown", "fox"]}';](https://image.slidesharecdn.com/cassandrav3-151208102757-lva1-app6892/85/Cassandra-v3-0-at-Rakuten-meet-up-on-12-2-2015-5-320.jpg)
![Deeper Nesting
INSERT INTO users JSON
'{"id": "0514e410-2a9f-11e5-a2cb-0800200c9a66",
"name": "jellis",
"addresses": {"home": {"street": "9920 Cassandra Ave",
"city": "Austin",
"zip_code": 78700,
"phones": ["1238614789"]}}}';](https://image.slidesharecdn.com/cassandrav3-151208102757-lva1-app6892/85/Cassandra-v3-0-at-Rakuten-meet-up-on-12-2-2015-8-320.jpg)
![UDF Aggregation
CREATE AGGREGATE avg (int)
SFUNC avgState
STYPE tuple<long, int>
FINALFUNC avgFinal;
CREATE FUNCTION avgState (state frozen<tuple<bigint, int>>, i int)
RETURNS frozen<tuple<bigint, int>>, int
LANGUAGE JAVA AS ’
// (state[0] + i, state[1] + 1)
state.setLong(0, state.getLong(0) + i.intValue());
state.setInt(1, state.getInt(1) + 1);
return state;
’;
CREATE FUNCTION avgFinal (state frozen<tuple<bigint, int>>)
RETURNS double
LANGUAGE JAVA AS ’
double r = state.getLong(0) / state.getInt(1);
return Double.valueOf(r);
’;](https://image.slidesharecdn.com/cassandrav3-151208102757-lva1-app6892/85/Cassandra-v3-0-at-Rakuten-meet-up-on-12-2-2015-11-320.jpg)
Cassandra v3.0 at Rakuten meet-up on 12/2/2015
- 2. Windows Support JSON UDF Role-based authz Commitlog Compression New Storage Engine New Hints Architecture Materialized Views DTCS Message Coalescing 3.0
- 3. Windows Support DTCS UDF Role-based authz Commitlog Compression New Storage Engine New Hints Architecture Materialized Views JSON Message Coalescing 2.2 3.0(July) (Released November 9)
- 4. JSON CREATE TABLE users ( id uuid PRIMARY KEY, name text, state text, birth_date int ); INSERT INTO users (id, name, state, birth_date) VALUES(now(), 'Joe User', 'TX', 1982); INSERT INTO users JSON '{"id": "1a4f88e2-6dc8-4edd-9e16-a7ba9c941f8d", "name": "Joe User", "state": "TX", "birth_date": 1982}';
- 5. 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']); INSERT INTO example JSON '{"id": 0, "tupleval": [1, "foo"], "numbers": [1, 2, 3, 6], "words": ["the", "quick", "brown", "fox"]}';
- 6. User-defined types 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'}); INSERT INTO users JSON '{"id": 1, "street_address": {"number": 1, "street": "Cassandra Ave"}}';
- 7. Deeper Nesting 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>> );
- 8. Deeper Nesting INSERT INTO users JSON '{"id": "0514e410-2a9f-11e5-a2cb-0800200c9a66", "name": "jellis", "addresses": {"home": {"street": "9920 Cassandra Ave", "city": "Austin", "zip_code": 78700, "phones": ["1238614789"]}}}';
- 9. Role-based Authorization CREATE ROLE accounting; GRANT all ON invoices TO accounting; GRANT select ON expenses TO accounting; GRANT select ON payroll TO accounting; GRANT accounting TO josie; GRANT accounting TO jay;
- 10. User-defined Functions (UDF) 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);
- 11. UDF Aggregation CREATE AGGREGATE avg (int) SFUNC avgState STYPE tuple<long, int> FINALFUNC avgFinal; CREATE FUNCTION avgState (state frozen<tuple<bigint, int>>, i int) RETURNS frozen<tuple<bigint, int>>, int LANGUAGE JAVA AS ’ // (state[0] + i, state[1] + 1) state.setLong(0, state.getLong(0) + i.intValue()); state.setInt(1, state.getInt(1) + 1); return state; ’; CREATE FUNCTION avgFinal (state frozen<tuple<bigint, int>>) RETURNS double LANGUAGE JAVA AS ’ double r = state.getLong(0) / state.getInt(1); return Double.valueOf(r); ’;
- 15. 3.0 Features
- 17. Pre 3.0 • Clustering keys are repeated for each cell • Timestamps are repeated in each cell • TTLS are.. you get the idea • Rows are a bolted on construct, only known by a convention • Lots of wasted space • Lots of repetition
- 18. Storage in 3.0 • Rows are a first class entity • Timestamps and TTLS can be stored on the Row • Clustering keys are not repeated • Conversion to iterators for memory efficiency
- 20. Pre 3.0 • Clustering keys are repeated for each cell • Timestamps are repeated in each cell • TTLS are.. you get the idea • Rows are a bolted on construct, only known by a convention • Lots of wasted space • Lots of repetition
- 21. Storage Model - Logical View 2005:12:1:10 -5.6 2005:12:1:9 -5.1 2005:12:1:8 -4.9 10010:99999 10010:99999 10010:99999 wsid hour temperature 2005:12:1:7 -5.3 10010:99999 SELECT wsid, hour, temperature FROM raw_weather_data WHERE wsid=‘10010:99999’ AND year = 2005 AND month = 12 AND day = 1;
- 22. 2005:12:1:10 -5.6 -5.3-4.9-5.1 Storage Model - Disk Layout 2005:12:1:9 2005:12:1:8 10010:99999 2005:12:1:7 SELECT wsid, hour, temperature FROM raw_weather_data WHERE wsid=‘10010:99999’ AND year = 2005 AND month = 12 AND day = 1; TTL Timestamp TTL Timestamp TTL Timestamp TTL Timestamp Repeated column values Repeated TTL and Timestamps
- 23. Storage in 3.0 • Rows are a first class entity • Timestamps and TTLS can be stored on the Row • Clustering keys are not repeated • Conversion to iterators for memory efficiency
- 28. SSTable-based Hints Hint Compacted Tombstone Memtable Commitlog SSTableCommitlog SSTable Memtable
- 31. 3.0 2.2 2.2 Hints vs 3.0Operations/s Time
- 32. Materialized Views CREATE TABLE songs ( id uuid PRIMARY KEY, title text, album text, artist text ); 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’;
- 33. Indexes CREATE TABLE songs ( id uuid PRIMARY KEY, title text, album text, artist text ); CREATE INDEX songs_by_album on songs(album); SELECT * FROM songs WHERE album = ‘Tres Hombres’;
- 34. 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
- 35. Materialized Views client album id Tres Hombres a3e64f8f Tres Hombres 8a172618 album id Roll Away 2b09185b
- 36. Stress: raw vs 1 MV vs 5 MV Operations/s Time raw 1 MV 5 MV
- 39. Beyond 3.0
- 40. JBOD-aware vnodes disk1 disk2 disk3 disk4
- 41. JBOD-aware vnodes disk1 disk2 disk3 disk4
- 43. 3.0 releases 3.0 rc1: Out now 3.0 GA November December 3.1 3.2 January February 3.3
- 44. 3.0 releases 3.0 rc1: Out now 3.0 GA October December 3.1 3.0.1 3.2 3.0.2 January February 3.3 3.0.3
- 46. DataStax Training for Apache Cassandra™