The document summarizes new features and improvements in Cassandra 2.0, including enhanced performance, scalability, and ease of use. Key updates include improved cursors for paging through large result sets, batching of prepared statements, simplified parameterized queries, additional CQL3 functionality, and lightweight transactions. Future plans outlined are secondary indexes on collections, more efficient repairs, custom data types, and aggregate functions in CQL. The document provides examples and explanations of new capabilities such as tracing, tombstone handling, and rapid read protection.

1. Cassandra 2.0
Lyuben Todorov
Cassandra Developer, DataStax

2. New Core Value
•
•
•
•
Massive Scalability
Performance
Reliability
Ease of Use

3. Binary Protocol

4. Binary Protocol
• Paging
• Batching prepared statements
• Improved parameterized statements

5. Cursors
Before - manual paging
• Have to keep track of position
• Complex for compound
primary keys
CREATE TABLE timeline (
...
PRIMARY KEY (uid, event_id)
);
SELECT * FROM timeline
WHERE (uid = :last_key
AND event_id > :last_event)
OR token(uid) >
token(:last_key)
LIMIT 100;

6. Cursors
Now
Statement s = new SimpleStatement(‚SELECT * FROM timeline‛);
s.setFetchSize(100);
// transparently fetches next pages
ResultSet result = session.execute(s);
for (Row row : result) {
dooStuff(row);
}

7. Cursors
Now
Statement s = new SimpleStatement(‚SELECT * FROM timeline‛);
s.setFetchSize(100);
// transparently fetches next pages
ResultSet result = session.execute(s);
for (Row row : result) {
dooStuff(row);
// x2
}

8. Batching PreparedStatement
PreparedStatement ps = session.prepare("INSERT INTO timeline
(id, event) VALUES(?, ?)");
BatchStatement batch = new BatchStatement();
batch.add(ps.bind(UUID.randomUUID(), event_1));
batch.add(ps.bind(UUID.randomUUID(), event_2));
session.execute(batch);

9. Simplified Parameterized Statements
session.execute(String cql, Object… values);
session.executeAsynch(String cql, Object… values);
session.execute("INSERT INTO timeline (uid, event)
VALUES (?, ?)", UUID.randomUUID(), event_x);

10. CQL3

11. CQL3
• SELECT DISTINCT partition_key;

12. CQL3
• SELECT DISTINCT partition_key;
• CREATE TABLE IF NOT EXISTS tbl_name;

13. CQL3
• SELECT DISTINCT partition_key;
• CREATE TABLE IF NOT EXISTS tbl_name;
• Aliases
SELECT event_id, dateOf(created_at) AS creation_date;

14. CQL3
• SELECT DISTINCT partition_key;
• CREATE TABLE IF NOT EXISTS tbl_name;
• Aliases
SELECT event_id, dateOf(created_at) AS creation_date
• ALTER TABLE tbl DROP column_name;

15. Lightweight Transactions
SESSION 1
SESSION 2
SELECT * FROM users
WHERE USERNAME = ‘lyuben’;
SELECT * FROM users
WHERE USERNAME = ‘lyuben’;
[empty resultset]
[empty resultset]
INSERT INTO users (...)
VALUES (‘lyubent’, ...)
INSERT INTO users (...)
VALUES (‘lyubent’, ...)
Last write wins.
User
exists?
If not,
create
user

16. Why not locking?
request
Client
(locks)
Coordinator
internal
request
Replica

17. Why not locking?
request
Client
(locks)
Coordinator
internal
request
X
Replica

18. Why not locking?
request
Coordinator
Client
(locks)
internal
request
store for replay
X
Replica

19. Why not locking?
request
Coordinator
Client
(locks)
internal
request
timeout
response
store for replay
X
Replica

20. Paxos
A family of protocols for solving consensus
in a network of unreliable processors.
Wikipedia

21. Paxos
• Immediate Consistency
• QUARUM based operations
• Unfinished operations’ states sent to leader
during prepare phase
• Paxos state is durable

22. LWT – Use when Appropriate
• Expensive – x4 round trips
• Eventual consistency is your friend

23. Lightweight Transactions – CQL
INSERT INTO USERS (username, email ...)
VALUES (‘lyuben’, ‘ltodorov@datastax.com’, ... )
IF NOT EXISTS;

24. Triggers
CREATE TRIGGER <name> ON <table> USING
<classname>;

25. Triggers
class MyTrigger implements ITrigger
{
public Collection<RowMutation> augment(ByteBuffer key, ColumnFamily update)
{
...
}
}

26. Tracing
• Detailed view of what’s going on
• Great for debugging queries
cqlsh:test> TRACING ON;
Now tracing requests.

27. Tracing insert
cqlsh:test> INSERT INTO example (i, j) VALUES ('key', 7);
Tracing session: 69fc9cb0-4fb3-11e3-84ae-612d9c5d36d9
activity
| timestamp
| source
| source_elapsed
------------------------------------+--------------+-----------+---------------Determining replicas for mutation | 18:09:34,722 | 127.0.0.1 |
3507
Sending message to /127.0.0.2 | 18:09:34,724 | 127.0.0.1 |
5720
Acquiring switchLock read lock | 18:09:34,732 | 127.0.0.2 |
6043
Appending to commitlog | 18:09:34,732 | 127.0.0.2 |
6305
Adding to example memtable | 18:09:34,732 | 127.0.0.2 |
6373
Enqueuing response to /127.0.0.1 | 18:09:34,733 | 127.0.0.2 |
6978
Message received from /127.0.0.2 | 18:09:34,737 | 127.0.0.1 |
19055
Processing response from /127.0.0.2 | 18:09:34,738 | 127.0.0.1 |
19993
Request complete | 18:09:34,739 | 127.0.0.1 |
20322

28. Tracing tombstone
cqlsh:test> SELECT * FROM example;
Tracing session: 79d55380-4fb7-11e3-9ac8-612d9c5d36d9
activity
| timestamp
| source
| source_elapsed
-----------------------------------------+--------------+-----------+--------------...
Sending message to /127.0.0.2 | 18:38:39,291 | 127.0.0.1 |
601
Read 10 live and 100000 tombstoned cells | 18:38:39,291 | 127.0.0.2 |
31655
Scanned 1 rows and matched 1 | 18:38:39,292 | 127.0.0.2 |
31693
Message received from /127.0.0.2 | 18:38:39,292 | 127.0.0.1 |
33150
Enqueuing response to /127.0.0.1 | 18:38:39,292 | 127.0.0.2 |
33724
Processing response from /127.0.0.2 | 18:38:39,292 | 127.0.0.1 |
34704
Sending message to /127.0.0.1 | 18:38:39,292 | 127.0.0.2 |
35220
...

29. Row Marker
CREATE TABLE tbl (
key int,
a text,
b text,
PRIMARY KEY (key)
);
UPDATE tbl SET a=null, b=null WHERE key=1;
DELETE FROM tbl where key=2;

30. Row Marker (JSON format)
[
{"key": "00000001","columns": [["","",1384716960173000],
["a","52891aa0",1384716960173000,"d"],
["b","52891aa0",1384716960173000,"d"]]
},
{"key": "00000002","columns": []}
]
Retreied via sstable2json

31. Rapid Read Protection
• Configurable per-table.
• Reduces occurrences of read timeouts in
overloaded / crashed replicas.
• Enabled by default in 2.0.2.

32. Rapid Read Protection

33. Rapid Read Protection
Configuring rapid read protection
# retry if request takes longer than 10ms
ALTER TABLE example WITH speculative_retry = '10ms';
# retry if request takes longer then 99% of requests
ALTER TABLE example WITH speculative_retry = '99percentile';

34. Going Off Heap
Managed by GC
Stack
Heap
Not Managed by GC
Native

35. Going Off Heap
• Bloom Filters
1 - 2GB per billion entries

36. Going Off Heap
• Bloom Filters
1 - 2GB per billion entries
• Compression Offsets
1 - 3GB per TB of compressed data

37. Going Off Heap
• Bloom Filters
1 - 2GB per billion entries
• Compression Offsets
1 - 3GB per TB of compressed data
• Partition Summary
Depends on # of rows per partition

38. Compaction
Leveled
Row fragments
Size Tiered

39. Leveled Compaction Strategy

40. Happy LCS

41. Sad LCS

42. STCS in Level 0

43. Coming up
• Secondary indexes for collections (4511)

44. Coming up
• Secondary indexes for collections (4511)
CREATE TABLE image (
id UUID,
tags set<text>,
PRIMARY KEY(id)
);
SELECT * FROM image WHERE tags CONTAINS ’sunny’;
image_id
| tags
--------------------------------------+------------------------------1a3ab520-5177-11e3-91ae-612d9c5d36d9 | {'beach', 'holiday', 'sunny'}
2617d120-5177-11e3-91ae-612d9c5d36d9 | {'mountains', 'sunny'}

45. Coming up
• Secondary indexes for collections (4511)
• More efficient repairs (5351)

46. Coming up
• Secondary indexes for collections (4511)
• More efficient repairs (5351)
STCS
Repair
Compaction

47. Coming up
• Secondary indexes for collections (4511)
• More efficient repairs (5351)
LCS
L0
L0
L1
L2

48. Coming up
• Secondary indexes for collections (4511)
• More efficient repairs (5351)
• Custom types (5590)

49. Coming up
• Secondary indexes for collections (4511)
• More efficient repairs (5351)
• Custom types (5590)
CREATE TYPE address (
street text,
city text,
zip_code int,
phones set<text>
)
Key
UTF8Type
UTF8Type
CREATE TABLE users (
id uuid PRIMARY KEY,
name text,
addresses map<int, address>
)
INT32Type
MapType ( Int32Type, Address)

50. Coming up
•
•
•
•
Secondary indexes for collections (4511)
More efficient repairs (5351)
Custom types (5590)
CQL aggregate functions (4914)

51. Coming up
•
•
•
•
Secondary indexes for collections (4511)
More efficient repairs (5351)
Custom types (5590)
CQL aggregate functions (4914)
– AVG, MIN, MAX, MEAN, SUM, etc.
SELECT sum(salary) FROM employee where country='UK';

52. Coming up
•
•
•
•
•
Secondary indexes for collections (4511)
More efficient repairs (5351)
Custom types (5590)
CQL aggregate functions (4914)
Many more!

53. DataStax Ac*ademy
Free online cassandra training!
https://datastaxacademy.elogiclearning.com/