1. Brisk: More Powerful Hadoop
Powered by Cassandra
jbellis@datastax.com
Monday, July 25, 2011

2. The evolution of Analytics
Analytics + Realtime
Monday, July 25, 2011

3. The evolution of Analytics
replication
Analytics Realtime
Monday, July 25, 2011

4. The evolution of Analytics
ETL
Monday, July 25, 2011

5. Brisk re-unifies realtime and analytics
Monday, July 25, 2011

6. The Traditional Hadoop Stack
Slave Nodes
Master Nodes
Data Node
Name Node
Task Tracker
Secondary Name Node
Region Server
Job Tracker
Hbase Master Client Nodes
Pig
ZooKeeper
Hive
MetaStore
Region Server
Monday, July 25, 2011

7. 7
Monday, July 25, 2011

8. Brisk Architecture
Monday, July 25, 2011

9. Brisk Highlights
✤ Easy to deploy and operate
✤ No single points of failure
✤ Scale and change nodes with no downtime
✤ Cross-DC, multi-master clusters
✤ Allocate resources for OLAP vs OLTP
✤ With no ETL
Monday, July 25, 2011

10. Cassandra data model
✤ ColumnFamilies contain rows + columns
✤ (Not really schemaless for a while now)
password name site
zznate * Nate McCall
driftx * Brandon Williams
jbellis * Jonathan Ellis datastax.com
Monday, July 25, 2011

11. Sparse
password name
zznate
* Nate McCall
password name
driftx
* Brandon Williams
password name site
jbellis
* Jonathan Ellis datastax.com
Monday, July 25, 2011

12. Rows as containers / materialized views
driftx thobbs pcmanus jbellis zznate
circle1
xedin mdennis
circle2
xedin pcmanus ymorishita
circle3
Monday, July 25, 2011

13. Monday, July 25, 2011

14. CassandraFS
✤ data stored as ByteBuffer internally -- excellent fit for blocks
✤ local reads mmap data directly (no rpc)
✤ blocks are compressed with google snappy
✤ hadoop distcp hdfs:///mydata cfs:///mydata
Monday, July 25, 2011

15. Hive support
✤ Hive MetaStore in Cassandra
✤ Unified schema view from any node, with no external systems
and no SPOF
✤ Automatically maps Cassandra column families to Hive tables
✤ Supports static and dynamic column families (and supercolumns)
Monday, July 25, 2011

16. Hive: CFS and ColumnFamilies
CREATE TABLE users (name STRING, zip INT);
LOAD DATA LOCAL INPATH 'kv2.txt' OVERWRITE INTO TABLE users;
CREATE EXTERNAL TABLE Keyspace1.Users(name STRING, zip INT)
STORED BY
'org.apache.hadoop.hive.cassandra.CassandraStorageHandler';
CREATE EXTERNAL TABLE Keyspace1.Users
(row_key STRING, column_name STRING, value string)
STORED BY
'org.apache.hadoop.hive.cassandra.CassandraStorageHandler';
Monday, July 25, 2011

17. Pig Support
✤ With standard Cassandra:
$ export PIG_HOME=/path/to/pig
$ export PIG_INITIAL_ADDRESS=localhost
$ export PIG_RPC_PORT=9160
$ export
PIG_PARTITIONER=org.apache.cassandra.dht.RandomPartitioner
$ contrib/pig/bin/pig_cassandra
grunt>
✤ With Brisk:
$ bin/brisk pig
grunt>
Monday, July 25, 2011

18. Pig: CFS and ColumnFamilies
grunt> data = LOAD 'cfs:///example.txt' using PigStorage() as
(name:chararray, value:long);
data = LOAD 'cassandra://Demo1/Scores' using CassandraStorage()
AS (key, columns: {T: tuple(name, value)});
data = LOAD 'cassandra://Demo1/Scores&slice_start=M&slice_end=S'
using CassandraStorage() AS (key, columns: {T: tuple(name,
value)});
Monday, July 25, 2011

19. 19
Monday, July 25, 2011

20. Data model: Realtime
LiveStocks
last
GOOG $95.52
AAPL $186.10
AMZN $112.98
Portfolios
GOOG LNKD P AMZN AAPLE
Portfolio1
80 20 40 100 20
StockHist
2011-01-01 2011-01-02 2011-01-03
GOOG
$79.85 $75.23 $82.11
Monday, July 25, 2011

21. Data model: Analytics
HistLoss
worst_date loss
Portfolio1 2011-07-23 -$34.81
Portfolio2 2011-03-11 -$11432.24
Portfolio3 2011-05-21 -$1476.93
Monday, July 25, 2011

22. Data model: Analytics
10dayreturns
ticker rdate return
GOOG 2011-07-25 $8.23
GOOG 2011-07-24 $6.14
GOOG 2011-07-23 $7.78
AAPL 2011-07-25 $15.32
AAPL 2011-07-24 $12.68
INSERT OVERWRITE TABLE 10dayreturns
SELECT a.row_key ticker,
b.column_name rdate,
b.value - a.value
FROM StockHist a
JOIN StockHist b
ON (a.row_key = b.row_key
AND date_add(a.column_name,10) = b.column_name);
Monday, July 25, 2011

23. 2011-01-01 2011-01-02 2011-01-03
GOOG
$79.85 $75.23 $82.11
row_key column_name value
GOOG 2011-01-01 $8.23
GOOG 2011-01-02 $6.14
GOOG 2011-001-03 $7.78
Monday, July 25, 2011

24. Data model: Analytics
portfolio_returns
portfolio rdate preturn
Portfolio1 2011-07-25 $118.21
Portfolio1 2011-07-24 $60.78
Portfolio1 2011-07-23 -$34.81
Portfolio2 2011-07-25 $2143.92
Portfolio3 2011-07-24 -$10.19
INSERT OVERWRITE TABLE portfolio_returns
SELECT row_key portfolio,
rdate,
SUM(b.return)
FROM portfolios a JOIN 10dayreturns b
ON (a.column_name = b.ticker)
GROUP BY row_key, rdate;
Monday, July 25, 2011

25. Data model: Analytics
HistLoss
worst_date loss
Portfolio1 2011-07-23 -$34.81
Portfolio2 2011-03-11 -$11432.24
Portfolio3 2011-05-21 -$1476.93
INSERT OVERWRITE TABLE HistLoss
SELECT a.portfolio, rdate, minp
FROM (
SELECT portfolio, min(preturn) as minp
FROM portfolio_returns
GROUP BY portfolio
) a
JOIN portfolio_returns b
ON (a.portfolio = b.portfolio and a.minp = b.preturn);
Monday, July 25, 2011

26. Portfolio Demo dataflow
Portfolios Web-based Portfolios
Historical Prices Live Prices for today
Intermediate Results
Largest loss Largest loss
Monday, July 25, 2011

27. OpsCenter
Monday, July 25, 2011

28. Monday, July 25, 2011

29. Where to get it
✤ http://www.datastax.com/brisk
Monday, July 25, 2011

30. Monday, July 25, 2011