SlideShare a Scribd company logo
1 of 92
Download to read offline
My Love of Developing
with the Postgres FDW
...and how production tested those feelings.
Jonathan S. Katz
PGConf EU 2015 - October 30, 2015
Hi! I'm Jonathan!
2
A Bit About Me
• @jkatz05
• Chief Technology Officer @ VenueBook
• Using Postgres since ~2004
• Been using it decently ~2010
• One day hope to use it well ;-)
• Active Postgres community member
• Co-Chair, PGConf US
• Co-organizer, NYC PostgreSQL User Group
• Director, United States PostgreSQL Association
• Have been to every PGConf.EU except Madrid :(
3
PGConf US 2016
April 18 - 20, New York City
http://www.pgconf.us/
4
Disclaimer
5
I loooooove PostgreSQL
Disclaimer #2
6
I'm some sort of weird dev / DBA / business-person hybrid
Okay, done with the boilerplate.
!
Let's do this.
7
Foreign Data Wrappers
in a Nutshell
• Provide a unified interface (i.e. SQL) to access
different data sources
• RDBMS (like Postgres!)
• NoSQL
• APIs (HTTP, Twitter, etc.)
• Internet of things
8
IMHO:
This is a killer feature
9
History of FDWs
• Released in 9.2 with a few read-only interfaces
• SQL-MED
• Did not include Postgres :(
• 9.3: Writeable FDWs
• ...and did include Postgres :D
• 9.4: Considers triggers on foreign tables
• 9.5
• IMPORT FOREIGN SCHEMA
• Push Down API (WIP)
• Inheritance children
10
Not Going Anywhere
• 9.6
• Join Push Down
• Aggregate API?
• Parallelism?
• "Hey we need some data from you, we will check
back later"
11
So I was just waiting for a
good problem to solve
with FDWs
12
And then a couple of
them came.
13
Some Background
14
VenueBook is revolutionizing the way
people think about event booking. Our
platform lets venues and bookers plan
together, creating a smarter and better-
connected experience for all. We simplify
planning, so you can have more fun!
Translation
• We have two main products:
• A CRM platform that allows venue managers to
control everything around an event.
• A marketplace that allows event planners source
venues and book events.
15
Further Translation
16
There are a lot of moving pieces with our data.
So The Following
Conversation Happend
17
18
Hey, can we build an API?
Sure, but I would want to run it as a
separate application so that way we can
isolate the load from our primary database.
Okay, that makes sense.
Great. There is a feature in Postgres that
makes it easy to talk between two separate
Postgres databases, so it shouldn't be too
difficult to build.
That sounds good. Let's do it!
There's one catch...
This could be a bit
experimental...
19
I want to experiment with this thing
called a "Foreign Data Wrapper"
but it should make maintenance
easier overall.
20
"OK"
21
Assumptions
• We are running PostgreSQL 9.4
• The schema I'm working with is slightly contrived
for the purposes of demonstration
23
So, let's build something
in our development
environment
24
25
local:app jkatz$ createuser!
Enter name of role to add: jkatz!
Shall the new role be a superuser? (y/n) y
Yeah, of course I want superuser
26
# "local" is for Unix domain socket connections only!
local all all trust
Yeah, of course I don't care about authentication settings.
(Pro-tip: "trust" means user privileges don't matter)
27
local:app jkatz$ createdb app
Let's pretend this is how I created the main database.
28
CREATE TABLE venues (
id serial PRIMARY KEY,
name varchar(255) NOT NULL
);
!
CREATE TABLE events (
id serial PRIMARY KEY,
venue_id int REFERENCES venues (id),
name text NOT NULL,
total int NOT NULL DEFAULT 0,
guests int NOT NULL,
start_time timestamptz NOT NULL,
end_time timestamptz NOT NULL,
created_at timestamptz DEFAULT CURRENT_TIMESTAMP NOT NULL
);
And let's pretend this is how I created the schema for it.
29
And this magic function to check for availability.
CREATE FUNCTION get_availability(
venue_id int,
start_time timestamptz,
end_time timestamptz
)
RETURNS bool
AS $$
SELECT NOT EXISTS(
SELECT 1
FROM events
WHERE
events.venue_id = $1 AND
($2, $3) OVERLAPS (events.start_time, events.end_time)
LIMIT 1
);
$$ LANGUAGE SQL STABLE;
30
local:app jkatz$ createdb api
So let's make the API schema
31
CREATE SCHEMA api;
We are going to be a bit smarter about
how we organize the code.
32
CREATE TABLE api.users (
id serial PRIMARY KEY,
key text UNIQUE NOT NULL,
name text NOT NULL
);
!
CREATE TABLE api.venues (
id serial PRIMARY KEY,
remote_venue_id int NOT NULL
);
!
CREATE TABLE api.events (
id serial PRIMARY KEY,
user_id int REFERENCES api.users (id) NOT NULL,
venue_id int REFERENCES api.venues (id) NOT NULL,
remote_bid_id text,
ip_address text,
data json,
created_at timestamptz DEFAULT CURRENT_TIMESTAMP NOT NULL
);
Our API schema
33
CREATE EXTENSION postgres_fdw;
!
CREATE SERVER app_server FOREIGN DATA WRAPPER postgres_fdw OPTIONS
(dbname 'app');
!
CREATE USER MAPPING FOR CURRENT_USER SERVER app_server;
Our setup to pull the information from the main application
34
CREATE SCHEMA app;
!
CREATE FOREIGN TABLE app.venues (
id int,
name text
) SERVER app_server OPTIONS (table_name 'venues');
We will isolate the foreign tables in their own schema
35
SELECT * FROM app.venues;
So that means this returns...
36
SELECT * FROM app.venues;
ERROR: relation "app.venues" does not exist
CONTEXT: Remote SQL command: SELECT id, name FROM app.venues
37
...what?
38
CREATE FOREIGN TABLE app.venues (
id int,
name text
) SERVER app_server OPTIONS (
table_name 'venues',
schema_name 'public'
);
If there is a schema mismatch between local and foreign table,
you have to set the schema explicitly.
39
SELECT * FROM app.venues;
id | name
----+--------------
1 | Venue A
2 | Restaurant B
3 | Bar C
4 | Club D
40
CREATE FOREIGN TABLE app.events (
id int,
venue_id int,
name text,
total int,
guests int,
start_time timestamptz,
end_time timestamptz
) SERVER app_server OPTIONS (
table_name 'events',
schema_name 'public'
);
Adding in our foreign table for events
41
INSERT INTO app.events (
venue_id,
name,
total,
guests,
start_time,
end_time
) VALUES (
1,
'Conference Party',
50000,
400,
'2015-10-28 18:00',
'2015-10-28 21:00'
)
RETURNING id;
ERROR: null value in column "id" violates not-null constraint
DETAIL: Failing row contains (null, 1, Conference Party, 50000, 400,
2015-10-28 22:00:00+00, 2015-10-29 01:00:00+00, 2015-10-27
22:19:10.555695+00).
CONTEXT: Remote SQL command: INSERT INTO public.events(id,
venue_id, name, total, guests, start_time, end_time) VALUES ($1, $2,
$3, $4, $5, $6, $7)
42
Huh.
43
Two Solutions.
44
Solution #1
45
CREATE FOREIGN TABLE app.events (
id serial NOT NULL,
venue_id int,
name text,
total int,
guests int,
start_time timestamptz,
end_time timestamptz
) SERVER app_server OPTIONS (
table_name 'events',
schema_name 'public'
);
46
INSERT INTO app.events (
venue_id,
name,
total,
guests,
start_time,
end_time
) VALUES (
1,
'Conference Party',
50000,
400,
'2015-10-28 18:00',
'2015-10-28 21:00'
)
RETURNING id;
id
----
1
(1 row)
WARNING
• This is using a sequence on the local database
• If you do not want to generate overlapping primary
keys, this is not the solution for you.
• Want to use the sequence generating function on
the foreign database
• But FDWs cannot access foreign functions
• However...
47
48
Solution #2
49
(on the "app" database)
CREATE SCHEMA api;
!
CREATE VIEW api.events_id_seq_view AS
SELECT nextval('public.events_id_seq') AS id;
50
CREATE FOREIGN TABLE app.events_id_seq_view (
id int
)
SERVER app_server
OPTIONS (
table_name 'events_id_seq_view',
schema_name 'api'
);
!
CREATE FUNCTION app.events_id_seq_nextval() RETURNS int AS $$
SELECT id FROM app.events_id_seq_view
$$ LANGUAGE SQL;
!
CREATE FOREIGN TABLE app.events (
id int DEFAULT app.events_id_seq_nextval(),
venue_id int,
name text,
total int,
guests int,
start_time timestamptz,
end_time timestamptz
) SERVER app_server OPTIONS (
table_name 'events',
schema_name 'public'
);
(on the "api" database)
51
INSERT INTO app.events (
venue_id,
name,
total,
guests,
start_time,
end_time
) VALUES (
1,
'Conference Party',
50000,
400,
'2015-10-28 18:00',
'2015-10-28 21:00'
)
RETURNING id;
id
----
4
(1 row)
52
Hey, can we check the availability on the api server
before making an insert on the app server?
53
Sure, we have a function for that on "app" but...
FDWs do not support foreign functions.
!
And we cannot use a view.
!
However...
dblink
• Written in 2001 by Joe Conway
• Designed to make remote PostgreSQL database
calls
• The docs say:
• See also postgres_fdw, which provides roughly
the same functionality using a more modern and
standards-compliant infrastructure.
54
55
-- setup the extensions (if not already done so)
CREATE EXTENSION plpgsql;
CREATE EXTENSION dblink;
!
-- create
CREATE FUNCTION app.get_availability(
venue_id int,
start_time timestamptz,
end_time timestamptz
)
RETURNS bool
AS $get_availability$
DECLARE
is_available bool;
remote_sql text;
BEGIN
remote_sql := format('SELECT get_availability(%L, %L, %L)', venue_id,
start_time, end_time);
SELECT availability.is_available
INTO is_available
FROM dblink('dbname=app', remote_sql) AS availability(is_available bool);
RETURN is_available;
EXCEPTION
WHEN others THEN
RETURN NULL::bool;
END;
$get_availability$ LANGUAGE plpgsql;
(on the "api" database)
56
SELECT app.get_availability(1, '2015-10-28 18:00', '2015-10-28 20:00');
get_availability
------------------
f
(1 row)
get_availability
------------------
t
(1 row)
SELECT app.get_availability(1, '2015-10-28 12:00', '2015-10-28 14:00');
Works great!
Summary So Far...
• We created two separate databases with logical schemas
• We wrote some code using postgres_fdw and dblink that
can
• Read data from "app" to "api"
• Insert data from "api" to the "app"
• ...with the help of the sequence trick
• Make a remote function call
57
Awesome!
Let's Deploy
58
(And because we are good developers,
we are going to test the deploy
configuration in a staging environment, but
we can all safely assume that, right? :-)
59
(Note: when I say
"superuser" I mean a
Postgres superuser)
60
61
app api
db01: 10.0.0.80
api
api01: 10.0.0.20
app
app01: 10.0.0.10
Network Topography
62
db01:postgresql postgres$ createdb -O app app!
db01:postgresql postgres$ createdb -O app api
How we are setting things up
63
# TYPE DATABASE USER ADDRESS METHOD
# for the main user
host app app 10.0.0.10/32 md5
host api api 10.0.0.20/32 md5
# for foreign table access
local api app md5
local app api md5
pg_hba.conf setup
64
CREATE EXTENSION postgres_fdw;
CREATE EXTENSION dblink;
So we already know to run these as a supuerser on "api" right?
;-)
65
CREATE SERVER app_server
FOREIGN DATA WRAPPER postgres_fdw
OPTIONS (dbname 'app');
ERROR: permission denied for foreign server app_server
But if we log in as the "api" user and try to run this...
66
As a superuser, grant permission
GRANT USAGE ON FOREIGN DATA WRAPPER postgres_fdw TO api;
67
CREATE SERVER app_server
FOREIGN DATA WRAPPER postgres_fdw
OPTIONS (dbname 'app');
!
CREATE FOREIGN TABLE app.venues (
id int,
name text
) SERVER app_server OPTIONS (
table_name 'venues',
schema_name 'public'
);
Now this works! Let's run a query...
68
SELECT * FROM app.venues;
ERROR: user mapping not found for "api"
69
CREATE USER MAPPING FOR api
SERVER app_server
OPTIONS (
user 'api',
password 'test'
);
So we create the user mapping and...
70
SELECT * FROM app.venues;
ERROR: permission denied for relation venues
CONTEXT: Remote SQL command: SELECT id, name FROM public.venues
You've got to be kidding me...
71
Go to "app" and as a superuser run this
GRANT SELECT ON venues TO api;
GRANT SELECT, INSERT, UPDATE ON events TO api;
72
SELECT * FROM app.venues;
id | name
----+--------------
1 | Venue A
2 | Restaurant B
3 | Bar C
4 | Club D
Meanwhile, back on "api"
Time to make the
events work.
73
74
CREATE SCHEMA api;
!
CREATE VIEW api.events_id_seq_view AS
SELECT nextval('public.events_id_seq') AS id;
Get things started on the "app" database
75
-- setup the sequence functionality
CREATE FOREIGN TABLE app.events_id_seq_view (
id int
)
SERVER app_server
OPTIONS (
table_name 'events_id_seq_view',
schema_name 'api'
);
!
CREATE FUNCTION app.events_id_seq_nextval() RETURNS int AS $$
SELECT id FROM app.events_id_seq_view
$$ LANGUAGE SQL;
Back on the "api" database
And when we test the
sequence function...
76
77
SELECT app.events_id_seq_nextval();
ERROR: permission denied for schema api
CONTEXT: Remote SQL command: SELECT id FROM api.events_id_seq_view
SQL function "events_id_seq_nextval" statement 1
Here we go again...
78
GRANT USAGE ON SCHEMA api TO api;
On the "app" database
79
SELECT app.events_id_seq_nextval();
ERROR: permission denied for relation events_id_seq_view
CONTEXT: Remote SQL command: SELECT id FROM api.events_id_seq_view
SQL function "events_id_seq_nextval" statement 1
On "api" - ARGH...
80
GRANT SELECT ON api.events_id_seq_view TO api;
On the "app" database
81
SELECT app.events_id_seq_nextval();
ERROR: permission denied for sequence events_id_seq
CONTEXT: Remote SQL command: SELECT id FROM api.events_id_seq_view
SQL function "events_id_seq_nextval" statement 1
On "api" - STILL?!?!?!?!
82
GRANT USAGE ON SEQUENCE events_id_seq TO api;
On the "app" database
83
SELECT app.events_id_seq_nextval();
And on "api" - YES!
events_id_seq_nextval
-----------------------
1
84
CREATE FOREIGN TABLE app.events (
id int DEFAULT app.events_id_seq_nextval(),
venue_id int,
name text,
total int,
guests int,
start_time timestamptz,
end_time timestamptz
) SERVER app_server OPTIONS (
table_name 'events',
schema_name 'public'
);
We can now create the foreign table and test the INSERT...
85
INSERT INTO app.events (
venue_id,
name,
total,
guests,
start_time,
end_time
) VALUES (
1,
'Conference Party',
50000,
400,
'2015-10-28 18:00',
'2015-10-28 21:00'
)
RETURNING id;
id
----
2
Yup...we ran "GRANT SELECT, INSERT, UPDATE ON events TO api;" on "app" earlier!
86
CREATE FUNCTION app.get_availability(
venue_id int,
start_time timestamptz,
end_time timestamptz
)
RETURNS bool
AS $get_availability$
DECLARE
is_available bool;
remote_sql text;
BEGIN
remote_sql := format('SELECT get_availability(%L, %L, %L)', venue_id, start_time,
end_time);
SELECT availability.is_available
INTO is_available
FROM dblink('dbname=app user=api password=test', remote_sql) AS
availability(is_available bool);
RETURN is_available;
EXCEPTION
WHEN others THEN
RETURN NULL::bool;
END;
$get_availability$ LANGUAGE plpgsql;
And install our availability function...
87
SELECT app.get_availability(1, '2015-10-28 18:00', '2015-10-28 20:00');
!
get_availability
------------------
f
(1 row)
!
!
SELECT app.get_availability(1, '2015-10-28 13:00', '2015-10-28 17:00');
!
get_availability
------------------
t
(1 row)
...and wow.
WE DID IT!!!
88
What did we learn?
89
We Learned That...
• PostgreSQL has a robust permission system
• http://www.postgresql.org/docs/current/static/sql-
grant.html
• ...there is much more we could have done too.
• Double the databases, double the problems
• Always have a testing environment that can mimic your
production environment
• ...when it all works, it is so sweet.
90
Conclusion
• Foreign data wrappers are incredible
• The postgres_fdw is incredible
• ...and it is still a work in progress
• Make sure you understand its limitations
• Research what is required to properly install in
production
91
Questions?
• @jkatz05
92

More Related Content

What's hot

Hive and Apache Tez: Benchmarked at Yahoo! Scale
Hive and Apache Tez: Benchmarked at Yahoo! ScaleHive and Apache Tez: Benchmarked at Yahoo! Scale
Hive and Apache Tez: Benchmarked at Yahoo! Scale
DataWorks Summit
 
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Simplilearn
 

What's hot (20)

Intro to Apache Spark
Intro to Apache SparkIntro to Apache Spark
Intro to Apache Spark
 
04 spark-pair rdd-rdd-persistence
04 spark-pair rdd-rdd-persistence04 spark-pair rdd-rdd-persistence
04 spark-pair rdd-rdd-persistence
 
Hive and Apache Tez: Benchmarked at Yahoo! Scale
Hive and Apache Tez: Benchmarked at Yahoo! ScaleHive and Apache Tez: Benchmarked at Yahoo! Scale
Hive and Apache Tez: Benchmarked at Yahoo! Scale
 
Introduction to HBase
Introduction to HBaseIntroduction to HBase
Introduction to HBase
 
Postgres vs Mongo / Олег Бартунов (Postgres Professional)
Postgres vs Mongo / Олег Бартунов (Postgres Professional)Postgres vs Mongo / Олег Бартунов (Postgres Professional)
Postgres vs Mongo / Олег Бартунов (Postgres Professional)
 
AF Ceph: Ceph Performance Analysis and Improvement on Flash
AF Ceph: Ceph Performance Analysis and Improvement on FlashAF Ceph: Ceph Performance Analysis and Improvement on Flash
AF Ceph: Ceph Performance Analysis and Improvement on Flash
 
NoSQL panorama - Jean Seiler Softeam
NoSQL panorama - Jean Seiler SofteamNoSQL panorama - Jean Seiler Softeam
NoSQL panorama - Jean Seiler Softeam
 
Introduction to Redis
Introduction to RedisIntroduction to Redis
Introduction to Redis
 
Key-Value NoSQL Database
Key-Value NoSQL DatabaseKey-Value NoSQL Database
Key-Value NoSQL Database
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDB
 
Introduction to Apache Spark Developer Training
Introduction to Apache Spark Developer TrainingIntroduction to Apache Spark Developer Training
Introduction to Apache Spark Developer Training
 
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
Hive Tutorial | Hive Architecture | Hive Tutorial For Beginners | Hive In Had...
 
Using Performance Insights to Optimize Database Performance (DAT402) - AWS re...
Using Performance Insights to Optimize Database Performance (DAT402) - AWS re...Using Performance Insights to Optimize Database Performance (DAT402) - AWS re...
Using Performance Insights to Optimize Database Performance (DAT402) - AWS re...
 
An Introduction to Elastic Search.
An Introduction to Elastic Search.An Introduction to Elastic Search.
An Introduction to Elastic Search.
 
A Rusty introduction to Apache Arrow and how it applies to a time series dat...
A Rusty introduction to Apache Arrow and how it applies to a  time series dat...A Rusty introduction to Apache Arrow and how it applies to a  time series dat...
A Rusty introduction to Apache Arrow and how it applies to a time series dat...
 
PySpark dataframe
PySpark dataframePySpark dataframe
PySpark dataframe
 
Apache Spark - Basics of RDD | Big Data Hadoop Spark Tutorial | CloudxLab
Apache Spark - Basics of RDD | Big Data Hadoop Spark Tutorial | CloudxLabApache Spark - Basics of RDD | Big Data Hadoop Spark Tutorial | CloudxLab
Apache Spark - Basics of RDD | Big Data Hadoop Spark Tutorial | CloudxLab
 
Apache Spark overview
Apache Spark overviewApache Spark overview
Apache Spark overview
 
CouchDB
CouchDBCouchDB
CouchDB
 
Spark Workshop
Spark WorkshopSpark Workshop
Spark Workshop
 

Similar to Developing and Deploying Apps with the Postgres FDW

Intravert Server side processing for Cassandra
Intravert Server side processing for CassandraIntravert Server side processing for Cassandra
Intravert Server side processing for Cassandra
Edward Capriolo
 
Parse cloud code
Parse cloud codeParse cloud code
Parse cloud code
維佋 唐
 

Similar to Developing and Deploying Apps with the Postgres FDW (20)

Cassandra and materialized views
Cassandra and materialized viewsCassandra and materialized views
Cassandra and materialized views
 
Application Monitoring using Open Source: VictoriaMetrics - ClickHouse
Application Monitoring using Open Source: VictoriaMetrics - ClickHouseApplication Monitoring using Open Source: VictoriaMetrics - ClickHouse
Application Monitoring using Open Source: VictoriaMetrics - ClickHouse
 
Application Monitoring using Open Source - VictoriaMetrics & Altinity ClickHo...
Application Monitoring using Open Source - VictoriaMetrics & Altinity ClickHo...Application Monitoring using Open Source - VictoriaMetrics & Altinity ClickHo...
Application Monitoring using Open Source - VictoriaMetrics & Altinity ClickHo...
 
GraphQL - an elegant weapon... for more civilized age
GraphQL - an elegant weapon... for more civilized ageGraphQL - an elegant weapon... for more civilized age
GraphQL - an elegant weapon... for more civilized age
 
Intravert Server side processing for Cassandra
Intravert Server side processing for CassandraIntravert Server side processing for Cassandra
Intravert Server side processing for Cassandra
 
NYC* 2013 - "Advanced Data Processing: Beyond Queries and Slices"
NYC* 2013 - "Advanced Data Processing: Beyond Queries and Slices"NYC* 2013 - "Advanced Data Processing: Beyond Queries and Slices"
NYC* 2013 - "Advanced Data Processing: Beyond Queries and Slices"
 
Build 2016 - B880 - Top 6 Reasons to Move Your C++ Code to Visual Studio 2015
Build 2016 - B880 - Top 6 Reasons to Move Your C++ Code to Visual Studio 2015Build 2016 - B880 - Top 6 Reasons to Move Your C++ Code to Visual Studio 2015
Build 2016 - B880 - Top 6 Reasons to Move Your C++ Code to Visual Studio 2015
 
Norikra: SQL Stream Processing In Ruby
Norikra: SQL Stream Processing In RubyNorikra: SQL Stream Processing In Ruby
Norikra: SQL Stream Processing In Ruby
 
Node azure
Node azureNode azure
Node azure
 
Big data week presentation
Big data week presentationBig data week presentation
Big data week presentation
 
Maciej Treder "Server-side rendering with Angular—be faster and more SEO, CDN...
Maciej Treder "Server-side rendering with Angular—be faster and more SEO, CDN...Maciej Treder "Server-side rendering with Angular—be faster and more SEO, CDN...
Maciej Treder "Server-side rendering with Angular—be faster and more SEO, CDN...
 
Yaetos Tech Overview
Yaetos Tech OverviewYaetos Tech Overview
Yaetos Tech Overview
 
EuroPython 2013 - FAST, DOCUMENTED AND RELIABLE JSON BASED WEBSERVICES WITH P...
EuroPython 2013 - FAST, DOCUMENTED AND RELIABLE JSON BASED WEBSERVICES WITH P...EuroPython 2013 - FAST, DOCUMENTED AND RELIABLE JSON BASED WEBSERVICES WITH P...
EuroPython 2013 - FAST, DOCUMENTED AND RELIABLE JSON BASED WEBSERVICES WITH P...
 
Novidades do c# 7 e 8
Novidades do c# 7 e 8Novidades do c# 7 e 8
Novidades do c# 7 e 8
 
SETCON'18 - Ilya labacheuski - GraphQL adventures
SETCON'18 - Ilya labacheuski - GraphQL adventuresSETCON'18 - Ilya labacheuski - GraphQL adventures
SETCON'18 - Ilya labacheuski - GraphQL adventures
 
Beyond Breakpoints: A Tour of Dynamic Analysis
Beyond Breakpoints: A Tour of Dynamic AnalysisBeyond Breakpoints: A Tour of Dynamic Analysis
Beyond Breakpoints: A Tour of Dynamic Analysis
 
Parse cloud code
Parse cloud codeParse cloud code
Parse cloud code
 
Monitoring Spark Applications
Monitoring Spark ApplicationsMonitoring Spark Applications
Monitoring Spark Applications
 
Horizontally Scalable Relational Databases with Spark: Spark Summit East talk...
Horizontally Scalable Relational Databases with Spark: Spark Summit East talk...Horizontally Scalable Relational Databases with Spark: Spark Summit East talk...
Horizontally Scalable Relational Databases with Spark: Spark Summit East talk...
 
.gradle 파일 정독해보기
.gradle 파일 정독해보기.gradle 파일 정독해보기
.gradle 파일 정독해보기
 

More from Jonathan Katz

Get Your Insecure PostgreSQL Passwords to SCRAM
Get Your Insecure PostgreSQL Passwords to SCRAMGet Your Insecure PostgreSQL Passwords to SCRAM
Get Your Insecure PostgreSQL Passwords to SCRAM
Jonathan Katz
 
Operating PostgreSQL at Scale with Kubernetes
Operating PostgreSQL at Scale with KubernetesOperating PostgreSQL at Scale with Kubernetes
Operating PostgreSQL at Scale with Kubernetes
Jonathan Katz
 

More from Jonathan Katz (15)

Vectors are the new JSON in PostgreSQL (SCaLE 21x)
Vectors are the new JSON in PostgreSQL (SCaLE 21x)Vectors are the new JSON in PostgreSQL (SCaLE 21x)
Vectors are the new JSON in PostgreSQL (SCaLE 21x)
 
Vectors are the new JSON in PostgreSQL
Vectors are the new JSON in PostgreSQLVectors are the new JSON in PostgreSQL
Vectors are the new JSON in PostgreSQL
 
Looking ahead at PostgreSQL 15
Looking ahead at PostgreSQL 15Looking ahead at PostgreSQL 15
Looking ahead at PostgreSQL 15
 
Build a Complex, Realtime Data Management App with Postgres 14!
Build a Complex, Realtime Data Management App with Postgres 14!Build a Complex, Realtime Data Management App with Postgres 14!
Build a Complex, Realtime Data Management App with Postgres 14!
 
High Availability PostgreSQL on OpenShift...and more!
High Availability PostgreSQL on OpenShift...and more!High Availability PostgreSQL on OpenShift...and more!
High Availability PostgreSQL on OpenShift...and more!
 
Get Your Insecure PostgreSQL Passwords to SCRAM
Get Your Insecure PostgreSQL Passwords to SCRAMGet Your Insecure PostgreSQL Passwords to SCRAM
Get Your Insecure PostgreSQL Passwords to SCRAM
 
Safely Protect PostgreSQL Passwords - Tell Others to SCRAM
Safely Protect PostgreSQL Passwords - Tell Others to SCRAMSafely Protect PostgreSQL Passwords - Tell Others to SCRAM
Safely Protect PostgreSQL Passwords - Tell Others to SCRAM
 
Operating PostgreSQL at Scale with Kubernetes
Operating PostgreSQL at Scale with KubernetesOperating PostgreSQL at Scale with Kubernetes
Operating PostgreSQL at Scale with Kubernetes
 
Building a Complex, Real-Time Data Management Application
Building a Complex, Real-Time Data Management ApplicationBuilding a Complex, Real-Time Data Management Application
Building a Complex, Real-Time Data Management Application
 
Using PostgreSQL With Docker & Kubernetes - July 2018
Using PostgreSQL With Docker & Kubernetes - July 2018Using PostgreSQL With Docker & Kubernetes - July 2018
Using PostgreSQL With Docker & Kubernetes - July 2018
 
An Introduction to Using PostgreSQL with Docker & Kubernetes
An Introduction to Using PostgreSQL with Docker & KubernetesAn Introduction to Using PostgreSQL with Docker & Kubernetes
An Introduction to Using PostgreSQL with Docker & Kubernetes
 
On Beyond (PostgreSQL) Data Types
On Beyond (PostgreSQL) Data TypesOn Beyond (PostgreSQL) Data Types
On Beyond (PostgreSQL) Data Types
 
Accelerating Local Search with PostgreSQL (KNN-Search)
Accelerating Local Search with PostgreSQL (KNN-Search)Accelerating Local Search with PostgreSQL (KNN-Search)
Accelerating Local Search with PostgreSQL (KNN-Search)
 
Webscale PostgreSQL - JSONB and Horizontal Scaling Strategies
Webscale PostgreSQL - JSONB and Horizontal Scaling StrategiesWebscale PostgreSQL - JSONB and Horizontal Scaling Strategies
Webscale PostgreSQL - JSONB and Horizontal Scaling Strategies
 
Indexing Complex PostgreSQL Data Types
Indexing Complex PostgreSQL Data TypesIndexing Complex PostgreSQL Data Types
Indexing Complex PostgreSQL Data Types
 

Recently uploaded

+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
?#DUbAI#??##{{(☎️+971_581248768%)**%*]'#abortion pills for sale in dubai@
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Safe Software
 

Recently uploaded (20)

A Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source MilvusA Beginners Guide to Building a RAG App Using Open Source Milvus
A Beginners Guide to Building a RAG App Using Open Source Milvus
 
presentation ICT roal in 21st century education
presentation ICT roal in 21st century educationpresentation ICT roal in 21st century education
presentation ICT roal in 21st century education
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law DevelopmentsTrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
TrustArc Webinar - Stay Ahead of US State Data Privacy Law Developments
 
A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?A Year of the Servo Reboot: Where Are We Now?
A Year of the Servo Reboot: Where Are We Now?
 
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
 
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
 
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot ModelNavi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
Navi Mumbai Call Girls 🥰 8617370543 Service Offer VIP Hot Model
 
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin WoodPolkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
 
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers:  A Deep Dive into Serverless Spatial Data and FMECloud Frontiers:  A Deep Dive into Serverless Spatial Data and FME
Cloud Frontiers: A Deep Dive into Serverless Spatial Data and FME
 
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
 
Corporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptxCorporate and higher education May webinar.pptx
Corporate and higher education May webinar.pptx
 
AWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of TerraformAWS Community Day CPH - Three problems of Terraform
AWS Community Day CPH - Three problems of Terraform
 
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
Apidays Singapore 2024 - Scalable LLM APIs for AI and Generative AI Applicati...
 

Developing and Deploying Apps with the Postgres FDW

  • 1. My Love of Developing with the Postgres FDW ...and how production tested those feelings. Jonathan S. Katz PGConf EU 2015 - October 30, 2015
  • 3. A Bit About Me • @jkatz05 • Chief Technology Officer @ VenueBook • Using Postgres since ~2004 • Been using it decently ~2010 • One day hope to use it well ;-) • Active Postgres community member • Co-Chair, PGConf US • Co-organizer, NYC PostgreSQL User Group • Director, United States PostgreSQL Association • Have been to every PGConf.EU except Madrid :( 3
  • 4. PGConf US 2016 April 18 - 20, New York City http://www.pgconf.us/ 4
  • 6. Disclaimer #2 6 I'm some sort of weird dev / DBA / business-person hybrid
  • 7. Okay, done with the boilerplate. ! Let's do this. 7
  • 8. Foreign Data Wrappers in a Nutshell • Provide a unified interface (i.e. SQL) to access different data sources • RDBMS (like Postgres!) • NoSQL • APIs (HTTP, Twitter, etc.) • Internet of things 8
  • 9. IMHO: This is a killer feature 9
  • 10. History of FDWs • Released in 9.2 with a few read-only interfaces • SQL-MED • Did not include Postgres :( • 9.3: Writeable FDWs • ...and did include Postgres :D • 9.4: Considers triggers on foreign tables • 9.5 • IMPORT FOREIGN SCHEMA • Push Down API (WIP) • Inheritance children 10
  • 11. Not Going Anywhere • 9.6 • Join Push Down • Aggregate API? • Parallelism? • "Hey we need some data from you, we will check back later" 11
  • 12. So I was just waiting for a good problem to solve with FDWs 12
  • 13. And then a couple of them came. 13
  • 14. Some Background 14 VenueBook is revolutionizing the way people think about event booking. Our platform lets venues and bookers plan together, creating a smarter and better- connected experience for all. We simplify planning, so you can have more fun!
  • 15. Translation • We have two main products: • A CRM platform that allows venue managers to control everything around an event. • A marketplace that allows event planners source venues and book events. 15
  • 16. Further Translation 16 There are a lot of moving pieces with our data.
  • 18. 18 Hey, can we build an API? Sure, but I would want to run it as a separate application so that way we can isolate the load from our primary database. Okay, that makes sense. Great. There is a feature in Postgres that makes it easy to talk between two separate Postgres databases, so it shouldn't be too difficult to build. That sounds good. Let's do it! There's one catch...
  • 19. This could be a bit experimental... 19
  • 20. I want to experiment with this thing called a "Foreign Data Wrapper" but it should make maintenance easier overall. 20
  • 22.
  • 23. Assumptions • We are running PostgreSQL 9.4 • The schema I'm working with is slightly contrived for the purposes of demonstration 23
  • 24. So, let's build something in our development environment 24
  • 25. 25 local:app jkatz$ createuser! Enter name of role to add: jkatz! Shall the new role be a superuser? (y/n) y Yeah, of course I want superuser
  • 26. 26 # "local" is for Unix domain socket connections only! local all all trust Yeah, of course I don't care about authentication settings. (Pro-tip: "trust" means user privileges don't matter)
  • 27. 27 local:app jkatz$ createdb app Let's pretend this is how I created the main database.
  • 28. 28 CREATE TABLE venues ( id serial PRIMARY KEY, name varchar(255) NOT NULL ); ! CREATE TABLE events ( id serial PRIMARY KEY, venue_id int REFERENCES venues (id), name text NOT NULL, total int NOT NULL DEFAULT 0, guests int NOT NULL, start_time timestamptz NOT NULL, end_time timestamptz NOT NULL, created_at timestamptz DEFAULT CURRENT_TIMESTAMP NOT NULL ); And let's pretend this is how I created the schema for it.
  • 29. 29 And this magic function to check for availability. CREATE FUNCTION get_availability( venue_id int, start_time timestamptz, end_time timestamptz ) RETURNS bool AS $$ SELECT NOT EXISTS( SELECT 1 FROM events WHERE events.venue_id = $1 AND ($2, $3) OVERLAPS (events.start_time, events.end_time) LIMIT 1 ); $$ LANGUAGE SQL STABLE;
  • 30. 30 local:app jkatz$ createdb api So let's make the API schema
  • 31. 31 CREATE SCHEMA api; We are going to be a bit smarter about how we organize the code.
  • 32. 32 CREATE TABLE api.users ( id serial PRIMARY KEY, key text UNIQUE NOT NULL, name text NOT NULL ); ! CREATE TABLE api.venues ( id serial PRIMARY KEY, remote_venue_id int NOT NULL ); ! CREATE TABLE api.events ( id serial PRIMARY KEY, user_id int REFERENCES api.users (id) NOT NULL, venue_id int REFERENCES api.venues (id) NOT NULL, remote_bid_id text, ip_address text, data json, created_at timestamptz DEFAULT CURRENT_TIMESTAMP NOT NULL ); Our API schema
  • 33. 33 CREATE EXTENSION postgres_fdw; ! CREATE SERVER app_server FOREIGN DATA WRAPPER postgres_fdw OPTIONS (dbname 'app'); ! CREATE USER MAPPING FOR CURRENT_USER SERVER app_server; Our setup to pull the information from the main application
  • 34. 34 CREATE SCHEMA app; ! CREATE FOREIGN TABLE app.venues ( id int, name text ) SERVER app_server OPTIONS (table_name 'venues'); We will isolate the foreign tables in their own schema
  • 35. 35 SELECT * FROM app.venues; So that means this returns...
  • 36. 36 SELECT * FROM app.venues; ERROR: relation "app.venues" does not exist CONTEXT: Remote SQL command: SELECT id, name FROM app.venues
  • 38. 38 CREATE FOREIGN TABLE app.venues ( id int, name text ) SERVER app_server OPTIONS ( table_name 'venues', schema_name 'public' ); If there is a schema mismatch between local and foreign table, you have to set the schema explicitly.
  • 39. 39 SELECT * FROM app.venues; id | name ----+-------------- 1 | Venue A 2 | Restaurant B 3 | Bar C 4 | Club D
  • 40. 40 CREATE FOREIGN TABLE app.events ( id int, venue_id int, name text, total int, guests int, start_time timestamptz, end_time timestamptz ) SERVER app_server OPTIONS ( table_name 'events', schema_name 'public' ); Adding in our foreign table for events
  • 41. 41 INSERT INTO app.events ( venue_id, name, total, guests, start_time, end_time ) VALUES ( 1, 'Conference Party', 50000, 400, '2015-10-28 18:00', '2015-10-28 21:00' ) RETURNING id; ERROR: null value in column "id" violates not-null constraint DETAIL: Failing row contains (null, 1, Conference Party, 50000, 400, 2015-10-28 22:00:00+00, 2015-10-29 01:00:00+00, 2015-10-27 22:19:10.555695+00). CONTEXT: Remote SQL command: INSERT INTO public.events(id, venue_id, name, total, guests, start_time, end_time) VALUES ($1, $2, $3, $4, $5, $6, $7)
  • 45. 45 CREATE FOREIGN TABLE app.events ( id serial NOT NULL, venue_id int, name text, total int, guests int, start_time timestamptz, end_time timestamptz ) SERVER app_server OPTIONS ( table_name 'events', schema_name 'public' );
  • 46. 46 INSERT INTO app.events ( venue_id, name, total, guests, start_time, end_time ) VALUES ( 1, 'Conference Party', 50000, 400, '2015-10-28 18:00', '2015-10-28 21:00' ) RETURNING id; id ---- 1 (1 row)
  • 47. WARNING • This is using a sequence on the local database • If you do not want to generate overlapping primary keys, this is not the solution for you. • Want to use the sequence generating function on the foreign database • But FDWs cannot access foreign functions • However... 47
  • 49. 49 (on the "app" database) CREATE SCHEMA api; ! CREATE VIEW api.events_id_seq_view AS SELECT nextval('public.events_id_seq') AS id;
  • 50. 50 CREATE FOREIGN TABLE app.events_id_seq_view ( id int ) SERVER app_server OPTIONS ( table_name 'events_id_seq_view', schema_name 'api' ); ! CREATE FUNCTION app.events_id_seq_nextval() RETURNS int AS $$ SELECT id FROM app.events_id_seq_view $$ LANGUAGE SQL; ! CREATE FOREIGN TABLE app.events ( id int DEFAULT app.events_id_seq_nextval(), venue_id int, name text, total int, guests int, start_time timestamptz, end_time timestamptz ) SERVER app_server OPTIONS ( table_name 'events', schema_name 'public' ); (on the "api" database)
  • 51. 51 INSERT INTO app.events ( venue_id, name, total, guests, start_time, end_time ) VALUES ( 1, 'Conference Party', 50000, 400, '2015-10-28 18:00', '2015-10-28 21:00' ) RETURNING id; id ---- 4 (1 row)
  • 52. 52 Hey, can we check the availability on the api server before making an insert on the app server?
  • 53. 53 Sure, we have a function for that on "app" but... FDWs do not support foreign functions. ! And we cannot use a view. ! However...
  • 54. dblink • Written in 2001 by Joe Conway • Designed to make remote PostgreSQL database calls • The docs say: • See also postgres_fdw, which provides roughly the same functionality using a more modern and standards-compliant infrastructure. 54
  • 55. 55 -- setup the extensions (if not already done so) CREATE EXTENSION plpgsql; CREATE EXTENSION dblink; ! -- create CREATE FUNCTION app.get_availability( venue_id int, start_time timestamptz, end_time timestamptz ) RETURNS bool AS $get_availability$ DECLARE is_available bool; remote_sql text; BEGIN remote_sql := format('SELECT get_availability(%L, %L, %L)', venue_id, start_time, end_time); SELECT availability.is_available INTO is_available FROM dblink('dbname=app', remote_sql) AS availability(is_available bool); RETURN is_available; EXCEPTION WHEN others THEN RETURN NULL::bool; END; $get_availability$ LANGUAGE plpgsql; (on the "api" database)
  • 56. 56 SELECT app.get_availability(1, '2015-10-28 18:00', '2015-10-28 20:00'); get_availability ------------------ f (1 row) get_availability ------------------ t (1 row) SELECT app.get_availability(1, '2015-10-28 12:00', '2015-10-28 14:00'); Works great!
  • 57. Summary So Far... • We created two separate databases with logical schemas • We wrote some code using postgres_fdw and dblink that can • Read data from "app" to "api" • Insert data from "api" to the "app" • ...with the help of the sequence trick • Make a remote function call 57
  • 59. (And because we are good developers, we are going to test the deploy configuration in a staging environment, but we can all safely assume that, right? :-) 59
  • 60. (Note: when I say "superuser" I mean a Postgres superuser) 60
  • 61. 61 app api db01: 10.0.0.80 api api01: 10.0.0.20 app app01: 10.0.0.10 Network Topography
  • 62. 62 db01:postgresql postgres$ createdb -O app app! db01:postgresql postgres$ createdb -O app api How we are setting things up
  • 63. 63 # TYPE DATABASE USER ADDRESS METHOD # for the main user host app app 10.0.0.10/32 md5 host api api 10.0.0.20/32 md5 # for foreign table access local api app md5 local app api md5 pg_hba.conf setup
  • 64. 64 CREATE EXTENSION postgres_fdw; CREATE EXTENSION dblink; So we already know to run these as a supuerser on "api" right? ;-)
  • 65. 65 CREATE SERVER app_server FOREIGN DATA WRAPPER postgres_fdw OPTIONS (dbname 'app'); ERROR: permission denied for foreign server app_server But if we log in as the "api" user and try to run this...
  • 66. 66 As a superuser, grant permission GRANT USAGE ON FOREIGN DATA WRAPPER postgres_fdw TO api;
  • 67. 67 CREATE SERVER app_server FOREIGN DATA WRAPPER postgres_fdw OPTIONS (dbname 'app'); ! CREATE FOREIGN TABLE app.venues ( id int, name text ) SERVER app_server OPTIONS ( table_name 'venues', schema_name 'public' ); Now this works! Let's run a query...
  • 68. 68 SELECT * FROM app.venues; ERROR: user mapping not found for "api"
  • 69. 69 CREATE USER MAPPING FOR api SERVER app_server OPTIONS ( user 'api', password 'test' ); So we create the user mapping and...
  • 70. 70 SELECT * FROM app.venues; ERROR: permission denied for relation venues CONTEXT: Remote SQL command: SELECT id, name FROM public.venues You've got to be kidding me...
  • 71. 71 Go to "app" and as a superuser run this GRANT SELECT ON venues TO api; GRANT SELECT, INSERT, UPDATE ON events TO api;
  • 72. 72 SELECT * FROM app.venues; id | name ----+-------------- 1 | Venue A 2 | Restaurant B 3 | Bar C 4 | Club D Meanwhile, back on "api"
  • 73. Time to make the events work. 73
  • 74. 74 CREATE SCHEMA api; ! CREATE VIEW api.events_id_seq_view AS SELECT nextval('public.events_id_seq') AS id; Get things started on the "app" database
  • 75. 75 -- setup the sequence functionality CREATE FOREIGN TABLE app.events_id_seq_view ( id int ) SERVER app_server OPTIONS ( table_name 'events_id_seq_view', schema_name 'api' ); ! CREATE FUNCTION app.events_id_seq_nextval() RETURNS int AS $$ SELECT id FROM app.events_id_seq_view $$ LANGUAGE SQL; Back on the "api" database
  • 76. And when we test the sequence function... 76
  • 77. 77 SELECT app.events_id_seq_nextval(); ERROR: permission denied for schema api CONTEXT: Remote SQL command: SELECT id FROM api.events_id_seq_view SQL function "events_id_seq_nextval" statement 1 Here we go again...
  • 78. 78 GRANT USAGE ON SCHEMA api TO api; On the "app" database
  • 79. 79 SELECT app.events_id_seq_nextval(); ERROR: permission denied for relation events_id_seq_view CONTEXT: Remote SQL command: SELECT id FROM api.events_id_seq_view SQL function "events_id_seq_nextval" statement 1 On "api" - ARGH...
  • 80. 80 GRANT SELECT ON api.events_id_seq_view TO api; On the "app" database
  • 81. 81 SELECT app.events_id_seq_nextval(); ERROR: permission denied for sequence events_id_seq CONTEXT: Remote SQL command: SELECT id FROM api.events_id_seq_view SQL function "events_id_seq_nextval" statement 1 On "api" - STILL?!?!?!?!
  • 82. 82 GRANT USAGE ON SEQUENCE events_id_seq TO api; On the "app" database
  • 83. 83 SELECT app.events_id_seq_nextval(); And on "api" - YES! events_id_seq_nextval ----------------------- 1
  • 84. 84 CREATE FOREIGN TABLE app.events ( id int DEFAULT app.events_id_seq_nextval(), venue_id int, name text, total int, guests int, start_time timestamptz, end_time timestamptz ) SERVER app_server OPTIONS ( table_name 'events', schema_name 'public' ); We can now create the foreign table and test the INSERT...
  • 85. 85 INSERT INTO app.events ( venue_id, name, total, guests, start_time, end_time ) VALUES ( 1, 'Conference Party', 50000, 400, '2015-10-28 18:00', '2015-10-28 21:00' ) RETURNING id; id ---- 2 Yup...we ran "GRANT SELECT, INSERT, UPDATE ON events TO api;" on "app" earlier!
  • 86. 86 CREATE FUNCTION app.get_availability( venue_id int, start_time timestamptz, end_time timestamptz ) RETURNS bool AS $get_availability$ DECLARE is_available bool; remote_sql text; BEGIN remote_sql := format('SELECT get_availability(%L, %L, %L)', venue_id, start_time, end_time); SELECT availability.is_available INTO is_available FROM dblink('dbname=app user=api password=test', remote_sql) AS availability(is_available bool); RETURN is_available; EXCEPTION WHEN others THEN RETURN NULL::bool; END; $get_availability$ LANGUAGE plpgsql; And install our availability function...
  • 87. 87 SELECT app.get_availability(1, '2015-10-28 18:00', '2015-10-28 20:00'); ! get_availability ------------------ f (1 row) ! ! SELECT app.get_availability(1, '2015-10-28 13:00', '2015-10-28 17:00'); ! get_availability ------------------ t (1 row) ...and wow.
  • 89. What did we learn? 89
  • 90. We Learned That... • PostgreSQL has a robust permission system • http://www.postgresql.org/docs/current/static/sql- grant.html • ...there is much more we could have done too. • Double the databases, double the problems • Always have a testing environment that can mimic your production environment • ...when it all works, it is so sweet. 90
  • 91. Conclusion • Foreign data wrappers are incredible • The postgres_fdw is incredible • ...and it is still a work in progress • Make sure you understand its limitations • Research what is required to properly install in production 91