This document discusses using PostgreSQL for a large database at Inmobi, an independent mobile ad network. It covers topics like partitioning the database into tables by date for improved performance, choosing indexes to optimize queries, ensuring high availability through streaming replication, and automating regular maintenance and archiving of old data.

1. Soumya Ranjan Subudhi
soumya.r.subudhi@gmail.com

2. The presenter ..
 Soumya Ranjan Subudhi
 Senior database engineer @ Inmobi
 Devops
LinkedIn : https://in.linkedin.com/in/soumyaranjansubudhi
Twitter : @soumyasubudhi

3. Today’s agenda
 Introduction
 Good for big database
 Current statistics
 Configurations
 Partitioning
 Indexing
 High availability
 Maintenance

4. Inmobi
 Independent mobile ad network
 Serves billions of ads with 1 billion monthly active
users and 30,000+ publishers

5. Dataflow
Metadata
Data enrichment
Data
.csv
generator
Publisher
tables
ETL
Advertiser
tables
Reporting database

6. Good for Big Databases
Scales
Low query latency
High availability
Easy maintenance

7. Few Stats
 Number of unique queries – 96,408
 Number of select queries per second – 3,455 qps
 Number of insert, update, delete queries per second
– 1217 qps
 Total number of sessions – 25,431
 Total number of sessions per second - 58

8. Few Stats

9. Few Stats

10. Few Stats

11. Configuration
 Use of SSDs
 Battery backed write cache
 Bigger readahead buffers
 Mounting partitions with noatime
 Raid 5 for WAL logs
 Raid 1+0 for data

12. Statistics
8 16 24
40
64
128 128
256
2 6 9 14
0
50
100
150
200
250
300
2012 2013 2014 2015
CPU (Number of processors) RAM (in GB) Database size (in TB)

13. Operations
Datafetch
Dataload
Most impacting operations

14. Jobs
 Hourly jobs
 Daily jobs
 Monthly jobs
 Quarterly jobs
 Report generation jobs
 Load monitoring jobs

15. How dataloading happen ?
 COPY , INSERT
 pg_bulkload, edbloader
 100k rows/minute

16. Partitioning
 Need for it
 Rule based
 A partition key
 Adding constraints

17. Partitioning
CREATE TABLE measurement (
city_id int not null,
logdate date not null,
peaktemp int,
unitsales int
);
CREATE TABLE measurement_y2006m02d01 (
CHECK ( logdate >= DATE '2006-02-01' AND logdate < DATE '2006-02-02' )
) INHERITS (measurement);
CREATE TABLE measurement_y2006m02d02 (
CHECK ( logdate >= DATE '2006-02-02' AND logdate < DATE '2006-02-03' )
) INHERITS (measurement);
CREATE TABLE measurement_y2006m02d03 (
CHECK ( logdate >= DATE '2006-02-03' AND logdate < DATE '2006-02-04' )
) INHERITS (measurement);
CREATE TABLE measurement_y2006m02d04 (
CHECK ( logdate >= DATE '2006-02-04' AND logdate < DATE '2006-02-05' )
) INHERITS (measurement);

18. Partitioning – Make it easy
 Automating :
 Partition creation
 Partition cleanup
CREATE TABLE measurement_y2006m02d01 (LIKE measurement
including indexes, CHECK (logdate >= '2006-02-01' AND logdate < DATE
'2006-02-02')) INHERITS (measurement);

19. Choosing indexes ..
 Listing Queries
 Optimizing queries
 Explain Analyzing

20. Choosing indexes ..
PREPARE query(int, int) AS SELECT sum(bar) FROM test
WHERE id > $1 AND id < $2
GROUP BY foo;
EXPLAIN ANALYZE EXECUTE query(100, 200);
QUERY PLAN
-------------------------------------------------------------------------------------------------------------------------
HashAggregate (cost=39.53..39.53 rows=1 width=8) (actual time=0.661..0.672 rows=7
loops=1)
-> Index Scan using test_pkey on test (cost=0.00..32.97 rows=1311 width=8) (actual
time=0.050..0.395 rows=99 loops=1)
Index Cond: ((id > $1) AND (id < $2))
Total runtime: 0.851 ms
(4 rows)

21. Archival and retention
 Set retention policy
 Jobs to automate archival
 Managed by puppet
 Need to pass parameters
 Send to “S3 bucket”
 Validate data
 No inherit child table from parent table and drop

22. High availability
 2 Servers
 Streaming replication
 Reporting packages (get synced by puppet)
 pgbouncer

23. Database fitness
 Vacuum analyze once a day
 Check bloat % and vacuum
 Offline
 Vacuum full
 Reindexing

24. What else …
 Monitoring and alerting - Nagios
 Graphing - graphite
 Stats - pgbadger

25. References
 http://www.enterprisedb.com/docs/en/9.3/oracompat/Postgres_Plus_
Advanced_Server_Oracle_Compatibility_Guide-217.htm
 http://www.postgresql.org/docs/9.2/static/ddl-partitioning.html
 http://www.postgresql.org/docs/9.2/static/pgbuffercache.html
 http://www.postgresql.org/docs/9.2/static/sql-explain.html