Don't panic! - Postgres introduction

Introduction to PostgreSQL
Don’t Panic!
Federico Campoli
Brighton PostgreSQL Users Group
13 June 2016
Federico Campoli (Brighton PostgreSQL Users Group) Introduction to PostgreSQL 13 June 2016 1 / 40

Table of contents
1 An elephant never forgets
2 A quick look to a powerful tool
3 NOSQL on Acid
4 Wrap up

An elephant never forgets
Table of contents
3 NOSQL on Acid
4 Wrap up

PostgreSQL, an history of excellence
Created at Berkeley in 1982 by database’s legend Prof. Stonebraker
In the 1994 Andrew Yu and Jolly Chen added the SQL interpreter
In the 1996 becomes an Open Source project.
The project’s name changes in PostgreSQL

Fully ACID compliant
High performance in read/write with the MVCC
Tablespaces

Tablespaces
Runs on almost any unix ﬂavour
From the version 8.0 is native on *cough* MS Windows *cough*
HA with hot standby and streaming replication
Heterogeneous federation

Tablespaces
Runs on almost any unix ﬂavour
From the version 8.0 is native on *cough* MS Windows *cough*
HA with hot standby and streaming replication
Heterogeneous federation
Procedural languages (pl/pgsql, pl/python, pl/perl...)
Support for NOSQL features like HSTORE and JSON

Development
Old ugly C language
New development cycle starts usually in June
New version released usually by the end of the year
At least 4 LTS versions
Can be extended using shared libraries
Extensions (9.1+)
BSD like license

Limits
Database size. No limits.
Table size 32 TB
Row size 1.6 TB
Field size 1 GB
Rows in table. No limits.
Fields in table 250 - 1600 depending on data type.
Tables in a database. No limits.

A quick look to a powerful tool
Table of contents
3 NOSQL on Acid
4 Wrap up

Image by Hein Waschefort -
http://commons.wikimedia.org/wiki/User:Hein waschefort

Data types
PostgreSQL comes with an incredibly rich data type set.

Data types
Numerical
smallint, integer, bigint
decimal, numeric, user-speciﬁed precision, exact
real,double precision, variable precision, inexact

Data types
Character
character
character varying with max size
text, character varying

Data types
Binary
bytea

Data types
Alongside the general purpose data types PostgreSQL have some exotic types.
Range (integers, date)
Geometric (points, lines etc.)
Network addresses
XML
JSON
JSONB
HSTORE (extension)

UPSERT (9.5+)
INSERT INTO t_table (i_id , v_value)
VALUES (1, ’fake value ’), (2, ’another fake value ’)
ON CONFLICT (i_id) DO UPDATE SET v_value = EXCLUDED.v_value;

Row Level Security (9.5+)
Row Level Security, allows security ”policies” ﬁltering rows per database user.

Big Data! (9.5+)
BIG DATA!
BRIN - Block Range Indices
IMPORT FOREIGN SCHEMA, Federation with steroids
TABLESAMPLE

GROUPING SETS
GROUPING SETS (shameless copied from the on line manual)
The data selected by the FROM and WHERE clauses is grouped separately by
each speciﬁed grouping set, aggregates computed for each group just as for simple
GROUP BY clauses, and then the results returned. For example:
=> SELECT * FROM items_sold;
brand | size | sales
-- -----+------+-------
Foo | L | 10
Foo | M | 20
Bar | M | 15
Bar | L | 5
(4 rows)
=> SELECT brand , size , sum(sales) FROM items_sold GROUP BY GROUPING SETS ((
brand), (size), ());
brand | size | sum
-- -----+------+-----
Foo | | 30
Bar | | 20
| L | 15
| M | 35
| | 50
(5 rows)

The future
PostgreSQL 9.6
Currently in beta
Parallel sequential scans, joins and aggregates
Push down for the postgresql foreigh data wrapper
Full text search for phrases, YAY!
Multiple synchronous standby servers
Snapshot too old!

NOSQL on Acid
Table of contents
3 NOSQL on Acid
4 Wrap up

NOSQL on Acid
NOSQL on Acid

NOSQL on Acid
JSON
JSON - JavaScript Object Notation
The version 9.2 adds JSON as native data type
The version 9.3 adds the support functions for JSON
JSON is stored as text
JSON is parsed and validated on the ﬂy
The 9.4 adds JSONB (binary) data type
The 9.5 improves JSONB

NOSQL on Acid
JSON
JSON - Examples
From record to JSON
postgres=# SELECT row_to_json(ROW(1,’foo’));
row_to_json
---------------------
{"f1":1,"f2":"foo"}
(1 row)
Expanding JSON into key to value elements
postgres=# SELECT * from json_each(’{"a":"foo", "b":"bar"}’);
key | value
-----+-------
a | "foo"
b | "bar"
(2 rows)

NOSQL on Acid
JSONB
Because JSON is parsed and validated on the ﬂy it could be a bottleneck.
The new JSONB introduced with PostgreSQL 9.4 is parsed, validated and
transformed at insert/update’s time. The access is then faster than the plain
JSON but the storage cost can be higher.
The functions available for JSON are also available in the JSONB ﬂavour.

NOSQL on Acid
Some numbers
Let’s create three tables with text,json and jsonb type ﬁelds.
Each record contains the same json element generated on
http://beta.json-generator.com/4kwCt-fwg
[ {
"_id": "56891aba27402de7f551bc91",
"index": 0,
"guid": "b9345045-1222-4f71-9540-6ed7c8d2ccae",
"isActive": false,
............
3,
{
"id": 1,
"name": "Bridgett Shaw"
}
],
"greeting": "Hello, Johnston! You have 8 unread messages.",
"favoriteFruit": "apple"
}
]Federico Campoli (Brighton PostgreSQL Users Group) Introduction to PostgreSQL 13 June 2016 25 / 40

NOSQL on Acid
Some numbers
DROP TABLE IF EXISTS t_json ;
DROP TABLE IF EXISTS t_jsonb ;
DROP TABLE IF EXISTS t_text ;
CREATE TABLE t_json as
SELECT
’<JSON ELEMENT >’:: json as js_value
FROM
generate_series (1 ,100000);
Query returned successfully : 100000 rows affected , 14504 ms execution time.
CREATE TABLE t_text as
SELECT
’<JSON ELEMENT >’:: text as t_value
FROM
CREATE TABLE t_jsonb as
SELECT
’<JSON ELEMENT >’:: jsonb as jsb_value
FROM

NOSQL on Acid
Table size
SELECT
pg_size_pretty ( pg_total_relation_size (oid)),
relname
FROM
pg_class
WHERE
relname LIKE ’t_%’
;
pg_size_pretty | relname
-- --------------+---------
270 MB | t_json
322 MB | t_jsonb
270 MB | t_text
(3 rows)

NOSQL on Acid
Sequential scans
TEXT
EXPLAIN (BUFFERS , ANALYZE) SELECT * FROM t_text;
Seq Scan on t_text (cost =0.00..1637.00 rows =100000 width =18) (actual time
=0.016..17.624 rows =100000 loops =1)
Buffers: shared hit =637
Planning time: 0.040 ms
Execution time: 28.967 ms
(4 rows)

NOSQL on Acid
Sequential scans
JSON
EXPLAIN (BUFFERS , ANALYZE) SELECT * FROM t_json;
Seq Scan on t_json (cost =0.00..1637.09 rows =100009 width =32) (actual time
=0.018..15.443 rows =100000 loops =1)
(4 rows)

NOSQL on Acid
Sequential scans
JSONB
EXPLAIN (BUFFERS , ANALYZE) SELECT * FROM t_jsonb;
Seq Scan on t_jsonb (cost =0.00..1637.00 rows =100000 width =18) (actual time
=0.015..18.943 rows =100000 loops =1)
(4 rows)

NOSQL on Acid
Sequential scan with json access
TEXT
EXPLAIN (BUFFERS , ANALYZE) SELECT t_value ::json ->’index ’ FROM t_text;
Seq Scan on t_text (cost =0.00..2387.00 rows =100000 width =18) (actual time
=0.159..7748.381 rows =100000 loops =1)
(4 rows)

NOSQL on Acid
JSON
EXPLAIN (BUFFERS , ANALYZE) SELECT js_value ->’index ’ FROM t_json;
Seq Scan on t_json (cost =0.00..1887.11 rows =100009 width =32) (actual time
=0.254..5787.267 rows =100000 loops =1)
(4 rows)

NOSQL on Acid
JSONB
EXPLAIN (BUFFERS , ANALYZE) SELECT jsb_value ->’index ’ FROM t_jsonb;
Seq Scan on t_jsonb (cost =0.00..1887.00 rows =100000 width =18) (actual time
=0.138..1678.222 rows =100000 loops =1)
(4 rows)

Wrap up
Table of contents
3 NOSQL on Acid
4 Wrap up

Wrap up
Wrap up
PostgreSQL is a powerful RDBMS with dozens of features and capabilities.
Choosing the correctly what to use can be tricky.
The lack of horizontal scalability in PostgreSQL can be a problem for large data
sets. However, an interesting project for a distributed cluster is PostgreSQL XL -
http://www.postgres-xl.org/
Another cool project is CitusDB, a powerful extension to add to PostgreSQL
horizontal scale capabilities.
CitusDB recently un-forked from PostgreSQL becoming an open source extension.
Yay!

Wrap up
Wrap up
Schema less data are useful. They are ﬂexible and powerful.
Never forget PostgreSQL is a RDBMS
Get a DBA on board

Wrap up
Questions
Questions?

Wrap up
Contacts
Twitter: 4thdoctor scarf
Personal blog: http://www.pgdba.co.uk
PostgreSQL Book:
http://www.slideshare.net/FedericoCampoli/postgresql-dba-01
Brighton PostgreSQL Meetup:
http://www.meetup.com/Brighton-PostgreSQL-Meetup/

Wrap up
License and copyright
This presentation is licensed under the terms of the Creative Commons
Attribution NonCommercial ShareAlike 4.0
http://creativecommons.org/licenses/by-nc-sa/4.0/
The cheetah photo is copyright by Hein Waschefort -
http://commons.wikimedia.org/wiki/User:Hein waschefort
The elephant logos are copyright of the PostgreSQL Global Development
Group - http://www.postgresql.org/

Wrap up
Introduction to PostgreSQL
Don’t Panic!
Federico Campoli
Brighton PostgreSQL Users Group
13 June 2016

Don't panic! - Postgres introduction

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