top five questions to ask when choosing a big data solution
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Five factors to consider when choosing a big data solution!Jonathan EllisCTO, DataStaxProject Chair, Apache Cassandra
©2012 DataStax
how do I
modelmy application?
©2012 DataStax
Popular options• Key/value
• Tabular
• Document
• Graph?
©2012 DataStax
Schema is your friend
{ "id": "e451dd42-ece3-11e1-a0a3-34159e154f4c", "name": "jbellis", "state": "TX", "birthdate": "1/1/1976", "email_addresses": ["jbellis@gmail", "[email protected]"],}
©2012 DataStax
SQL can be your friend too
CREATE TABLE users ( id uuid PRIMARY KEY, name text, state text, birth_date date);
CREATE INDEX ON users(state);
SELECT * FROM usersWHERE state=‘Texas’ AND birth_date > ‘1950-01-01’;
©2012 DataStax
CREATE TABLE users ( id uuid PRIMARY KEY, name text, state text, birth_date date);
CREATE TABLE users_addresses ( user_id uuid REFERENCES users, email text);
SELECT *FROM users NATURAL JOIN users_addresses;
Collections
©2012 DataStax
CREATE TABLE users ( id uuid PRIMARY KEY, name text, state text, birth_date date);
CREATE TABLE users_addresses ( user_id uuid REFERENCES users, email text);
SELECT *FROM users NATURAL JOIN users_addresses;
Collections
X
©2012 DataStax
CREATE TABLE users ( id uuid PRIMARY KEY, name text, state text, birth_date date, email_addresses set<text>);
UPDATE usersSET email_addresses = email_addresses + {‘[email protected]’, ‘[email protected]’};
Collections
©2012 DataStax
Joins don’t scale• No joins
• No subqueries
• No aggregation functions* or GROUP BY
• ORDER BY?
©2012 DataStax
SELECT * FROM tweetsWHERE user_id IN (SELECT follower FROM followers WHERE user_id = ’driftx’)
followers
?
tweets
©2012 DataStax
CREATE TABLE timeline ( user_id uuid, tweet_id timeuuid, tweet_author uuid, tweet_body text, PRIMARY KEY (user_id, tweet_id));
Clustering in Cassandrauser_id tweet_id _author _body
jbellis 3290f9da.. rbranson loremjbellis 3895411a.. tjake ipsum
... ... ...
driftx 3290f9da.. rbranson loremdriftx 71b46a84.. yzhang dolor
... ... ...
yukim 3290f9da.. rbranson loremyukim e451dd42.. tjake amet
... ... ...
©2012 DataStax
CREATE TABLE timeline ( user_id uuid, tweet_id timeuuid, tweet_author uuid, tweet_body text, PRIMARY KEY (user_id, tweet_id));
Clustering in Cassandrauser_id tweet_id _author _body
jbellis 3290f9da.. rbranson loremjbellis 3895411a.. tjake ipsum
... ... ...
driftx 3290f9da.. rbranson loremdriftx 71b46a84.. yzhang dolor
... ... ...
yukim 3290f9da.. rbranson loremyukim e451dd42.. tjake amet
... ... ...
SELECT * FROM timelineWHERE user_id = ’driftx’;
©2012 DataStax
how does it
perform?
©2012 DataStax
Larger than memory datasets
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Locking
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Efficiency
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UPDATE usersSET email_addresses = email_addresses + {...}WHERE user_id = ‘jbellis’;
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Durability
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C* storage engine very briefly
Memory
Hard drive
Memtable
write( , )k1 c1:v1
Commit log
©2012 DataStax
Memory
Hard drive
Memtable
write( , )k1 c1:v1
Commit log
k1 c1:v1
k1 c1:v1
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Memory
Hard drive
write( , )k1 c2:v2
k1 c1:v1
k1 c1:v1
k1 c2:v2
c2:v2
©2012 DataStax
Memory
Hard drive
k1 c1:v1
k1 c1:v1
k1 c2:v2
c2:v2
write( , )k2 c1:v1 c2:v2
k2 c1:v1 c2:v2
k2 c1:v1 c2:v2
©2012 DataStax
Memory
Hard drive
k1 c1:v1
k1 c1:v4
k1 c2:v2
c2:v2
write( , )k1 c1:v4 c3:v3
k2 c1:v1 c2:v2
k2 c1:v1 c2:v2
k1 c1:v4 c3:v3
c3:v3
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Memory
Hard drive
SSTable
flush
k1 c1:v4 c2:v2
k2 c1:v1 c2:v2
c3:v3
index
cleanup
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No random writes
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0
5000
10000
15000
20000
25000
30000
35000
Cassandra 0.6
Cassandra 1.0
reads/s writes/s
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how does it handle
failure?
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Classic partitioning with SPOFpartition 1 partition 2 partition 3 partition 4
router
client
©2012 DataStax
Availability• “High availability implies that a single fault will not bring
down your system. Not ‘we’ll recover quickly.’” -- Ben Coverston: DataStax
• “The biggest problem with failover is that you're almost never using it until it really hurts. It's like backups that you never test.” -- Rick Branson: Instagram
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Fully distributed, no SPOFclient
p1
p1
p1p3
p6
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Multiple datacenters
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how does it
scale?
©2012 DataStax
Scaling antipatterns• Metadata servers
• Router bottlenecks
• Overloading existing nodes when adding capacity
©2012 DataStax
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how
flexibleis it?
36
©2012 DataStax
Data model: Realtime
Portfolios
StockHist
stock lastGOOG $95.52AAPL $186.10AMZN $112.98
LiveStocks
stock date priceGOOG 2011-01-01 $8.23GOOG 2011-01-02 $6.14GOOG 2011-001-03 $7.78
user stock sharesjbellis GOOG 80jbellis LNKD 20yukim AMZN 100
©2012 DataStax
Data model: Analytics
worst_date loss2011-07-23 -$34.812011-03-11 -$11432.242011-05-21 -$1476.93
Portfolio1
HistLoss
Portfolio2Portfolio3
©2012 DataStax
Data model: Analyticsstock rdate returnGOOG 2011-07-25 $8.23GOOG 2011-07-24 $6.14GOOG 2011-07-23 $7.78AAPL 2011-07-25 $15.32AAPL 2011-07-24 $12.68
10dayreturns
INSERT OVERWRITE TABLE 10dayreturnsSELECT a.stock, b.date as rdate, b.price - a.priceFROM StockHist a JOIN StockHist b ON (a.stock = b.stock AND date_add(a.date, 10) = b.date);
©2012 DataStax
Data model: Analytics
portfolio rdate preturnPortfolio1 2011-07-25 $118.21Portfolio1 2011-07-24 $60.78Portfolio1 2011-07-23 -$34.81Portfolio2 2011-07-25 $2143.92Portfolio3 2011-07-24 -$10.19
portfolio_returns
INSERT OVERWRITE TABLE portfolio_returnsSELECT portfolio, rdate, SUM(b.return)FROM portfolios a JOIN 10dayreturns b ON (a.stock = b.stock)GROUP BY portfolio, rdate;
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Data model: Analytics
INSERT OVERWRITE TABLE HistLossSELECT a.portfolio, rdate, minpFROM ( 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);
worst_date loss2011-07-23 -$34.812011-03-11 -$11432.242011-05-21 -$1476.93
Portfolio1
HistLoss
Portfolio2Portfolio3
42
©2012 DataStax
Some Cassandra users
Questions?
• http://www.!ickr.com/photos/26817893@N05/2573006312/
• http://www.!ickr.com/photos/rowanbank/7686239548
• http://www.!ickr.com/photos/mervtheswerve/6081933265
• http://www.!ickr.com/photos/dg_pics/2526208830
• http://www.!ickr.com/photos/wainwright/351684037
• http://www.!ickr.com/photos/mikeneilson/1606662529
• http://www.!ickr.com/photos/sbisson/3852905534
• http://www.!ickr.com/photos/breadnbadger/2674928517
Image credits