SlideShare uma empresa Scribd logo
1 de 40
Baixar para ler offline
PostgreSQL 9.3 and JSON
Andrew Dunstan
andrew@dunslane.net
andrew.dunstan@pgexperts.com
Overview
● What is JSON?
● Why use JSON?
● Quick review of 9.2 features
● 9.3 new features
● Building on 9.3 features
● Some useful extensions
● Future work
What is JSON?
● Data serialization format
● Lightweight
● Human readable
● Becoming ubiquitous
● Simpler and more compact than XML
What it looks like
{
"books" : [
{ "title": "Catch 22”, "author": "Joseph Heller"},
{ "title": "Catcher in the Rye", "author": "J. D. Salinger"}
],
"publishers": [
{ "name": "Random House" },
{ "name": "Penguin" }
],
"active": true,
"version": 35,
"date": "2003-09-13",
“reference”: null
}
Scalars:
● quoted strings
● numbers
● true, false, null
No extensions
No date/time types
Why use it?
● Everyone is moving that way
● Understood everywhere there is a JavaScript
interpreter
– Especially browsers
● ... and in a large number of other languages
– e.g. Perl, Python
● node.js is becoming very widely used
● More compact than XML
● Most applications don't need the richer
structure of XML
Why not use it?
● Overly verbose
● Field names are repeated
● Arguably less readable than, say, YAML
● Not suitable for huge objects
Review – pre 9.2 facilities
Nothing – store JSON as text
● No validation
● No JSON production
● No JSON extraction
Review – 9.2 data type
New JSON type
● Stored as text
● Reasonably performant state-based validating
parser
● Kudos: Robert Haas
Review – 9.2 production functions
● Turn non-JSON data into JSON
● row_to_json(anyrecord)
● array_to_json(anyarray)
● Optional second param for pretty printing
● My humble contribution ☺
What's missing?
● JSON production features are incomplete
● JSON processing is totally absent
● Have to use PLV8, PLPerl or some such
9.3 Features – JSON production
● to_json(any)
● Can be used on any datum, not just
arrays and records
● json_agg(record)
● Much faster than
array_to_json(array_agg(record))
9.3 and casts to JSON
● Production functions honor casts to JSON
for non-builtin types
● Not needed for builtins, as we know how
to convert them
● Saves syscache lookups where we know
it's not necessary
9.3 hstore and JSON
● hstore_to_json(hstore)
● Also used as a cast function
● hstore_to_json_loose(hstore)
● Uses heuristics about whether or not
certain possibly numeric and boolean
values need to be quoted.
9.3 JSON parser rewrite
● New parser uses recursive descent
pattern
● Caller can supply event handlers for
certain events
● c.f. XML SAX parsers
● Validator uses NULL handlers for all
events
● Tokenizing routines of previous parser
largely kept
9.3 JSON processsing functions
● All leverage new parser API
● Operators give a more natural style to
extraction operations
● Many have two forms, producing either
JSON output, which can be further
processed, or text output, which cannot.
● Text output is de-escaped and dequoted
9.3 extraction operators (1)
● -> fetch an array element or object
member as json
● '[4,5,6]'::json->2 ⟹ 6
– json arrays are 0 based, unlike SQL arrays
● '{"a":1,"b":2}'::json->'b' ⟹ 2
9.3 extraction operators (2)
● ->> fetch an array element orobject
member as text
● '["a","b","c"]'::json->2 ⟹ c
– Instead of "c"
9.3 extraction operators (3)
● #> and #>> fetch data pointed at by a
path
● Path is an array of text elements
● Treats arrays correctly by some trying to
treat path element as an integer of
necessary
● '{"a":[6,7,8]}'::json#>'{a,1}' ⟹ 7
●
9.3 extraction functions
● json_extract_path(json, VARIADIC
path_elems text[]);
● json_extract_path_text(json, VARIADIC
path_elems text[]);
● Same as #> and #>> operators, but
you can pass the path as a variadic
array
● json_extract_path('{"a":[6,7,8]}','a','1')
⟹ 7
9.3 turn JSON into records
● CREATE TYPE x AS (a int, b int);
● SELECT * FROM
json_populate_record(null::x,
'{"a":1,"b":2}', false);
● SELECT * FROM
json_populate_recordset(null::x,'[{"a":1,"
b":2},{"a":3,"b":4}]', false);
9.3 turn JSON into key/value pairs
● SELECT * FROM
json_each('{"a":1,"b":"foo"}')
● SELECT * FROM
json_each_text('{"a":1,"b":"foo"}')
● Deliver columns named “key” and
“value”
9.3 get keys from JSON object
● SELECT * FROM
json_object_keys('{"a":1,"b":"foo"}')
9.3 JSON array processing
● SELECT json_array_length('[1,2,3,4]');
● SELECT * FROM
json_array_elements('[1,2,3,4]')
9.3 the JSON C API
● Need
● A state object
● Some handlers
● Stash these in a JsonSemAction object
● call pg_json_parse()
9.3 API example
● Code can be cloned from
https://bitbucket.org/adunstan/json_typeof
● CREATE FUNCTION json_typeof(json)
RETURNS text
AS 'MODULE_PATHNAME'
LANGUAGE C STRICT IMMUTABLE;
9.3 API example state object
● #include <utils/jsonapi.h>
● typedef struct typeof_state {
JsonLexContext *lex;
JsonTokenType result;
} TypeofState;
9.3 API example event handlers
● Need one for each of:
● Array start
● Object start
● Scalar
9.3 API example array/object
start handlers
● static void json_typeof_astart (void *state)
{
TypeofState *_state = (TypeofState *) state;
if (_state->lex->lex_level == 0)
_state->result = JSON_TOKEN_ARRAY_START;
}
static void json_typeof_ostart (void *state)
{
TypeofState *_state = (TypeofState *) state;
if (_state->lex->lex_level == 0)
_state->result = JSON_TOKEN_OBJECT_START;
}
9.3 API example scalar handler
● static void json_typeof_scalar(
void *state,
char *token,
JsonTokenType tokentype)
{
TypeofState *_state = (TypeofState *) state;
if (_state->lex->lex_level == 0)
_state->result = tokentype;
}
9.3 example function code
Datum json_typeof(PG_FUNCTION_ARGS)
{
text *json = PG_GETARG_TEXT_P(0);
TypeofState *state;
JsonLexContext *lex = makeJsonLexContext(json, false);
JsonSemAction *sem;
state = palloc0(sizeof(TypeofState));
sem = palloc0(sizeof(JsonSemAction));
state->lex = lex;
sem->semstate = (void *) state;
sem->object_start = json_typeof_ostart;
sem->array_start = json_typeof_astart;
sem->scalar = json_typeof_scalar;
pg_parse_json(lex, sem);
PG_RETURN_TEXT_P(token_to_type(state->result));
}
9.3 CAPI – what else is it good for?
● Transformations of all kinds
● XML
● YAML
● ....
● An XML transformation was the original
working model for creating the API
Other useful modules
● Developed for use by my clients
● json_build lets you compose json of arbitrary
complexity
● json_object creates a json object from a 1- or
2-dimensional array of text, similar to hstore
facility.
json_build
● Two functions:
● build_json_object(VARIADIC “any”)
● build_json_array(VARIADIC “any”)
● Together these let you compose deeply nested
tree structures safely.
json_build example
SELECT build_json_object(
'a', build_json_object('b',false,'c',99),
'd', build_json_object('e',array[9,8,7]::int[],
'f', (select row_to_json(r) from
( select relkind, oid::regclass as name
from pg_class where relname = 'pg_class') r)));
{"a" : {"b" : false, "c" : 99}, "d" : {"e" : [9,8,7],
"f" : {"relkind":"r","name":"pg_class"}}}
json_object examples
SELECT json_object('{a,1,b,2,3,NULL,"d e f","a b c"}');
json_object
-------------------------------------------------------
{"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"}
-- same but with two dimensions
SELECT json_object('{{a,1},{b,2},{3,NULL},{"d e f","a b c"}}');
json_object
-------------------------------------------------------
{"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"}
json_object examples
SELECT json_object('{a,1,b,2,3,NULL,"d e f","a b c"}');
json_object
-------------------------------------------------------
{"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"}
-- same but with two dimensions
SELECT json_object('{{a,1},{b,2},{3,NULL},{"d e f","a b c"}}');
json_object
-------------------------------------------------------
{"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"}
Extension repos
● https://github.com/pgexperts/json_build
● https://bitbucket.org/qooleot/json_object
● Also on PGXN
Future of JSON in PostgreSQL
● Possible binary representation
● Avoid reparsing
● Could be vastly faster for some operations
● Should we use a dictionary and store structure
separately?
● General document store
● Need to get around the “rewrite a whole
datum” issue
Credit
● 9.3 core development work sponsored by
Heroku
● Other work sponsored by PGExperts clients
and IVC
Questions?

Mais conteúdo relacionado

Mais procurados

Shell Tips & Tricks
Shell Tips & TricksShell Tips & Tricks
Shell Tips & Tricks
MongoDB
 
Superficial mongo db
Superficial mongo dbSuperficial mongo db
Superficial mongo db
DaeMyung Kang
 
iOS: Web Services and XML parsing
iOS: Web Services and XML parsingiOS: Web Services and XML parsing
iOS: Web Services and XML parsing
Jussi Pohjolainen
 
Nosql hands on handout 04
Nosql hands on handout 04Nosql hands on handout 04
Nosql hands on handout 04
Krishna Sankar
 

Mais procurados (20)

Redis data modeling examples
Redis data modeling examplesRedis data modeling examples
Redis data modeling examples
 
Getting Started with MongoDB
Getting Started with MongoDBGetting Started with MongoDB
Getting Started with MongoDB
 
Shell Tips & Tricks
Shell Tips & TricksShell Tips & Tricks
Shell Tips & Tricks
 
Node js crash course session 6
Node js crash course   session 6Node js crash course   session 6
Node js crash course session 6
 
MongoDB - Ekino PHP
MongoDB - Ekino PHPMongoDB - Ekino PHP
MongoDB - Ekino PHP
 
ClojureScript for the web
ClojureScript for the webClojureScript for the web
ClojureScript for the web
 
Node.js and angular js
Node.js and angular jsNode.js and angular js
Node.js and angular js
 
JavaScript client API for Google Apps Script API primer
JavaScript client API for Google Apps Script API primerJavaScript client API for Google Apps Script API primer
JavaScript client API for Google Apps Script API primer
 
Javascript forloop-let
Javascript forloop-letJavascript forloop-let
Javascript forloop-let
 
Herding types with Scala macros
Herding types with Scala macrosHerding types with Scala macros
Herding types with Scala macros
 
Superficial mongo db
Superficial mongo dbSuperficial mongo db
Superficial mongo db
 
Full Stack Clojure
Full Stack ClojureFull Stack Clojure
Full Stack Clojure
 
MongoDB.local DC 2018: Ch-Ch-Ch-Ch-Changes: Taking Your MongoDB Stitch Applic...
MongoDB.local DC 2018: Ch-Ch-Ch-Ch-Changes: Taking Your MongoDB Stitch Applic...MongoDB.local DC 2018: Ch-Ch-Ch-Ch-Changes: Taking Your MongoDB Stitch Applic...
MongoDB.local DC 2018: Ch-Ch-Ch-Ch-Changes: Taking Your MongoDB Stitch Applic...
 
Mondodb
MondodbMondodb
Mondodb
 
ClojureScript loves React, DomCode May 26 2015
ClojureScript loves React, DomCode May 26 2015ClojureScript loves React, DomCode May 26 2015
ClojureScript loves React, DomCode May 26 2015
 
20150724 jason winston js
20150724 jason winston js20150724 jason winston js
20150724 jason winston js
 
iOS: Web Services and XML parsing
iOS: Web Services and XML parsingiOS: Web Services and XML parsing
iOS: Web Services and XML parsing
 
New text document
New text documentNew text document
New text document
 
Nosql hands on handout 04
Nosql hands on handout 04Nosql hands on handout 04
Nosql hands on handout 04
 
Querying mongo db
Querying mongo dbQuerying mongo db
Querying mongo db
 

Destaque

Keith Paskett - Postgres on ZFS @ Postgres Open
Keith Paskett - Postgres on ZFS @ Postgres OpenKeith Paskett - Postgres on ZFS @ Postgres Open
Keith Paskett - Postgres on ZFS @ Postgres Open
PostgresOpen
 
David Keeney - SQL Database Server Requests from the Browser @ Postgres Open
David Keeney - SQL Database Server Requests from the Browser @ Postgres OpenDavid Keeney - SQL Database Server Requests from the Browser @ Postgres Open
David Keeney - SQL Database Server Requests from the Browser @ Postgres Open
PostgresOpen
 
Kevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres OpenKevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres Open
PostgresOpen
 
Craig Kerstiens - Scalable Uniques in Postgres @ Postgres Open
Craig Kerstiens - Scalable Uniques in Postgres @ Postgres OpenCraig Kerstiens - Scalable Uniques in Postgres @ Postgres Open
Craig Kerstiens - Scalable Uniques in Postgres @ Postgres Open
PostgresOpen
 
Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...
Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...
Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...
PostgresOpen
 
Keith Fiske - When PostgreSQL Can't, You Can @ Postgres Open
Keith Fiske - When PostgreSQL Can't, You Can @ Postgres OpenKeith Fiske - When PostgreSQL Can't, You Can @ Postgres Open
Keith Fiske - When PostgreSQL Can't, You Can @ Postgres Open
PostgresOpen
 
Bruce Momjian - Inside PostgreSQL Shared Memory @ Postgres Open
Bruce Momjian - Inside PostgreSQL Shared Memory @ Postgres OpenBruce Momjian - Inside PostgreSQL Shared Memory @ Postgres Open
Bruce Momjian - Inside PostgreSQL Shared Memory @ Postgres Open
PostgresOpen
 

Destaque (7)

Keith Paskett - Postgres on ZFS @ Postgres Open
Keith Paskett - Postgres on ZFS @ Postgres OpenKeith Paskett - Postgres on ZFS @ Postgres Open
Keith Paskett - Postgres on ZFS @ Postgres Open
 
David Keeney - SQL Database Server Requests from the Browser @ Postgres Open
David Keeney - SQL Database Server Requests from the Browser @ Postgres OpenDavid Keeney - SQL Database Server Requests from the Browser @ Postgres Open
David Keeney - SQL Database Server Requests from the Browser @ Postgres Open
 
Kevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres OpenKevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter - PostgreSQL Backup and Recovery Methods @ Postgres Open
 
Craig Kerstiens - Scalable Uniques in Postgres @ Postgres Open
Craig Kerstiens - Scalable Uniques in Postgres @ Postgres OpenCraig Kerstiens - Scalable Uniques in Postgres @ Postgres Open
Craig Kerstiens - Scalable Uniques in Postgres @ Postgres Open
 
Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...
Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...
Gurjeet Singh - How Postgres is Different From (Better Tha) Your RDBMS @ Post...
 
Keith Fiske - When PostgreSQL Can't, You Can @ Postgres Open
Keith Fiske - When PostgreSQL Can't, You Can @ Postgres OpenKeith Fiske - When PostgreSQL Can't, You Can @ Postgres Open
Keith Fiske - When PostgreSQL Can't, You Can @ Postgres Open
 
Bruce Momjian - Inside PostgreSQL Shared Memory @ Postgres Open
Bruce Momjian - Inside PostgreSQL Shared Memory @ Postgres OpenBruce Momjian - Inside PostgreSQL Shared Memory @ Postgres Open
Bruce Momjian - Inside PostgreSQL Shared Memory @ Postgres Open
 

Semelhante a Andrew Dunstan 9.3 JSON Presentation @ Postgres Open 2013

json.ppt download for free for college project
json.ppt download for free for college projectjson.ppt download for free for college project
json.ppt download for free for college project
AmitSharma397241
 
Oh, that ubiquitous JSON !
Oh, that ubiquitous JSON !Oh, that ubiquitous JSON !
Oh, that ubiquitous JSON !
Alexander Korotkov
 
MongoDB and Web Scrapping with the Gyes Platform
MongoDB and Web Scrapping with the Gyes PlatformMongoDB and Web Scrapping with the Gyes Platform
MongoDB and Web Scrapping with the Gyes Platform
MongoDB
 
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
 

Semelhante a Andrew Dunstan 9.3 JSON Presentation @ Postgres Open 2013 (20)

9.4json
9.4json9.4json
9.4json
 
json.ppt download for free for college project
json.ppt download for free for college projectjson.ppt download for free for college project
json.ppt download for free for college project
 
Oh, that ubiquitous JSON !
Oh, that ubiquitous JSON !Oh, that ubiquitous JSON !
Oh, that ubiquitous JSON !
 
Postgres-XC as a Key Value Store Compared To MongoDB
Postgres-XC as a Key Value Store Compared To MongoDBPostgres-XC as a Key Value Store Compared To MongoDB
Postgres-XC as a Key Value Store Compared To MongoDB
 
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
 
MongoDB and Web Scrapping with the Gyes Platform
MongoDB and Web Scrapping with the Gyes PlatformMongoDB and Web Scrapping with the Gyes Platform
MongoDB and Web Scrapping with the Gyes Platform
 
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"
 
Mongoskin - Guilin
Mongoskin - GuilinMongoskin - Guilin
Mongoskin - Guilin
 
Getting Input from User
Getting Input from UserGetting Input from User
Getting Input from User
 
Unit-2 Getting Input from User.pptx
Unit-2 Getting Input from User.pptxUnit-2 Getting Input from User.pptx
Unit-2 Getting Input from User.pptx
 
Working with JSON
Working with JSONWorking with JSON
Working with JSON
 
Groovy.pptx
Groovy.pptxGroovy.pptx
Groovy.pptx
 
[2019-07] GraphQL in depth (serverside)
[2019-07] GraphQL in depth (serverside)[2019-07] GraphQL in depth (serverside)
[2019-07] GraphQL in depth (serverside)
 
Introduction to MongoDB
Introduction to MongoDBIntroduction to MongoDB
Introduction to MongoDB
 
2011 Mongo FR - MongoDB introduction
2011 Mongo FR - MongoDB introduction2011 Mongo FR - MongoDB introduction
2011 Mongo FR - MongoDB introduction
 
Compiling EdgeQL
Compiling EdgeQLCompiling EdgeQL
Compiling EdgeQL
 
Bind me if you can
Bind me if you canBind me if you can
Bind me if you can
 
An Introduction to Postgresql
An Introduction to PostgresqlAn Introduction to Postgresql
An Introduction to Postgresql
 
Tour de Jackson: Forgotten Features of Jackson JSON processor
Tour de Jackson: Forgotten Features of Jackson JSON processorTour de Jackson: Forgotten Features of Jackson JSON processor
Tour de Jackson: Forgotten Features of Jackson JSON processor
 

Mais de PostgresOpen

Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...
Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...
Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...
PostgresOpen
 
Steve Singer - Managing PostgreSQL with Puppet @ Postgres Open
Steve Singer - Managing PostgreSQL with Puppet @ Postgres OpenSteve Singer - Managing PostgreSQL with Puppet @ Postgres Open
Steve Singer - Managing PostgreSQL with Puppet @ Postgres Open
PostgresOpen
 
John Melesky - Federating Queries Using Postgres FDW @ Postgres Open
John Melesky - Federating Queries Using Postgres FDW @ Postgres OpenJohn Melesky - Federating Queries Using Postgres FDW @ Postgres Open
John Melesky - Federating Queries Using Postgres FDW @ Postgres Open
PostgresOpen
 
Koichi Suzuki - Postgres-XC Dynamic Cluster Management @ Postgres Open
Koichi Suzuki - Postgres-XC Dynamic Cluster  Management @ Postgres OpenKoichi Suzuki - Postgres-XC Dynamic Cluster  Management @ Postgres Open
Koichi Suzuki - Postgres-XC Dynamic Cluster Management @ Postgres Open
PostgresOpen
 
Selena Deckelmann - Sane Schema Management with Alembic and SQLAlchemy @ Pos...
Selena Deckelmann - Sane Schema Management with  Alembic and SQLAlchemy @ Pos...Selena Deckelmann - Sane Schema Management with  Alembic and SQLAlchemy @ Pos...
Selena Deckelmann - Sane Schema Management with Alembic and SQLAlchemy @ Pos...
PostgresOpen
 
Robert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres Open
Robert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres OpenRobert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres Open
Robert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres Open
PostgresOpen
 
Michael Paquier - Taking advantage of custom bgworkers @ Postgres Open
Michael Paquier - Taking advantage of custom bgworkers @ Postgres OpenMichael Paquier - Taking advantage of custom bgworkers @ Postgres Open
Michael Paquier - Taking advantage of custom bgworkers @ Postgres Open
PostgresOpen
 
Kevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres OpenKevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres Open
PostgresOpen
 
Michael Bayer Introduction to SQLAlchemy @ Postgres Open
Michael Bayer Introduction to SQLAlchemy @ Postgres OpenMichael Bayer Introduction to SQLAlchemy @ Postgres Open
Michael Bayer Introduction to SQLAlchemy @ Postgres Open
PostgresOpen
 
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres OpenRobert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
PostgresOpen
 
Ryan Jarvinen Open Shift Talk @ Postgres Open 2013
Ryan Jarvinen Open Shift Talk @ Postgres Open 2013Ryan Jarvinen Open Shift Talk @ Postgres Open 2013
Ryan Jarvinen Open Shift Talk @ Postgres Open 2013
PostgresOpen
 

Mais de PostgresOpen (11)

Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...
Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...
Henrietta Dombrovskaya - A New Approach to Resolve Object-Relational Impedanc...
 
Steve Singer - Managing PostgreSQL with Puppet @ Postgres Open
Steve Singer - Managing PostgreSQL with Puppet @ Postgres OpenSteve Singer - Managing PostgreSQL with Puppet @ Postgres Open
Steve Singer - Managing PostgreSQL with Puppet @ Postgres Open
 
John Melesky - Federating Queries Using Postgres FDW @ Postgres Open
John Melesky - Federating Queries Using Postgres FDW @ Postgres OpenJohn Melesky - Federating Queries Using Postgres FDW @ Postgres Open
John Melesky - Federating Queries Using Postgres FDW @ Postgres Open
 
Koichi Suzuki - Postgres-XC Dynamic Cluster Management @ Postgres Open
Koichi Suzuki - Postgres-XC Dynamic Cluster  Management @ Postgres OpenKoichi Suzuki - Postgres-XC Dynamic Cluster  Management @ Postgres Open
Koichi Suzuki - Postgres-XC Dynamic Cluster Management @ Postgres Open
 
Selena Deckelmann - Sane Schema Management with Alembic and SQLAlchemy @ Pos...
Selena Deckelmann - Sane Schema Management with  Alembic and SQLAlchemy @ Pos...Selena Deckelmann - Sane Schema Management with  Alembic and SQLAlchemy @ Pos...
Selena Deckelmann - Sane Schema Management with Alembic and SQLAlchemy @ Pos...
 
Robert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres Open
Robert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres OpenRobert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres Open
Robert Bernier - Recovering From A Damaged PostgreSQL Cluster @ Postgres Open
 
Michael Paquier - Taking advantage of custom bgworkers @ Postgres Open
Michael Paquier - Taking advantage of custom bgworkers @ Postgres OpenMichael Paquier - Taking advantage of custom bgworkers @ Postgres Open
Michael Paquier - Taking advantage of custom bgworkers @ Postgres Open
 
Kevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres OpenKevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres Open
Kevin Kempter PostgreSQL Backup and Recovery Methods @ Postgres Open
 
Michael Bayer Introduction to SQLAlchemy @ Postgres Open
Michael Bayer Introduction to SQLAlchemy @ Postgres OpenMichael Bayer Introduction to SQLAlchemy @ Postgres Open
Michael Bayer Introduction to SQLAlchemy @ Postgres Open
 
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres OpenRobert Haas Query Planning Gone Wrong Presentation @ Postgres Open
Robert Haas Query Planning Gone Wrong Presentation @ Postgres Open
 
Ryan Jarvinen Open Shift Talk @ Postgres Open 2013
Ryan Jarvinen Open Shift Talk @ Postgres Open 2013Ryan Jarvinen Open Shift Talk @ Postgres Open 2013
Ryan Jarvinen Open Shift Talk @ Postgres Open 2013
 

Último

Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
WSO2
 
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
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
 

Último (20)

DBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor PresentationDBX First Quarter 2024 Investor Presentation
DBX First Quarter 2024 Investor Presentation
 
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ..."I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
 
Architecting Cloud Native Applications
Architecting Cloud Native ApplicationsArchitecting Cloud Native Applications
Architecting Cloud Native Applications
 
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
 
2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...2024: Domino Containers - The Next Step. News from the Domino Container commu...
2024: Domino Containers - The Next Step. News from the Domino Container commu...
 
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
 
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
Apidays New York 2024 - APIs in 2030: The Risk of Technological Sleepwalk by ...
 
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUKSpring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
 
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
 
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
 
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
 
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWEREMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
EMPOWERMENT TECHNOLOGY GRADE 11 QUARTER 2 REVIEWER
 
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
 
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectorsMS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
 
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
 
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with MilvusExploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
 
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
Navigating the Deluge_ Dubai Floods and the Resilience of Dubai International...
 
Exploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone ProcessorsExploring the Future Potential of AI-Enabled Smartphone Processors
Exploring the Future Potential of AI-Enabled Smartphone Processors
 

Andrew Dunstan 9.3 JSON Presentation @ Postgres Open 2013

  • 1. PostgreSQL 9.3 and JSON Andrew Dunstan andrew@dunslane.net andrew.dunstan@pgexperts.com
  • 2. Overview ● What is JSON? ● Why use JSON? ● Quick review of 9.2 features ● 9.3 new features ● Building on 9.3 features ● Some useful extensions ● Future work
  • 3. What is JSON? ● Data serialization format ● Lightweight ● Human readable ● Becoming ubiquitous ● Simpler and more compact than XML
  • 4. What it looks like { "books" : [ { "title": "Catch 22”, "author": "Joseph Heller"}, { "title": "Catcher in the Rye", "author": "J. D. Salinger"} ], "publishers": [ { "name": "Random House" }, { "name": "Penguin" } ], "active": true, "version": 35, "date": "2003-09-13", “reference”: null } Scalars: ● quoted strings ● numbers ● true, false, null No extensions No date/time types
  • 5. Why use it? ● Everyone is moving that way ● Understood everywhere there is a JavaScript interpreter – Especially browsers ● ... and in a large number of other languages – e.g. Perl, Python ● node.js is becoming very widely used ● More compact than XML ● Most applications don't need the richer structure of XML
  • 6. Why not use it? ● Overly verbose ● Field names are repeated ● Arguably less readable than, say, YAML ● Not suitable for huge objects
  • 7. Review – pre 9.2 facilities Nothing – store JSON as text ● No validation ● No JSON production ● No JSON extraction
  • 8. Review – 9.2 data type New JSON type ● Stored as text ● Reasonably performant state-based validating parser ● Kudos: Robert Haas
  • 9. Review – 9.2 production functions ● Turn non-JSON data into JSON ● row_to_json(anyrecord) ● array_to_json(anyarray) ● Optional second param for pretty printing ● My humble contribution ☺
  • 10. What's missing? ● JSON production features are incomplete ● JSON processing is totally absent ● Have to use PLV8, PLPerl or some such
  • 11. 9.3 Features – JSON production ● to_json(any) ● Can be used on any datum, not just arrays and records ● json_agg(record) ● Much faster than array_to_json(array_agg(record))
  • 12. 9.3 and casts to JSON ● Production functions honor casts to JSON for non-builtin types ● Not needed for builtins, as we know how to convert them ● Saves syscache lookups where we know it's not necessary
  • 13. 9.3 hstore and JSON ● hstore_to_json(hstore) ● Also used as a cast function ● hstore_to_json_loose(hstore) ● Uses heuristics about whether or not certain possibly numeric and boolean values need to be quoted.
  • 14. 9.3 JSON parser rewrite ● New parser uses recursive descent pattern ● Caller can supply event handlers for certain events ● c.f. XML SAX parsers ● Validator uses NULL handlers for all events ● Tokenizing routines of previous parser largely kept
  • 15. 9.3 JSON processsing functions ● All leverage new parser API ● Operators give a more natural style to extraction operations ● Many have two forms, producing either JSON output, which can be further processed, or text output, which cannot. ● Text output is de-escaped and dequoted
  • 16. 9.3 extraction operators (1) ● -> fetch an array element or object member as json ● '[4,5,6]'::json->2 ⟹ 6 – json arrays are 0 based, unlike SQL arrays ● '{"a":1,"b":2}'::json->'b' ⟹ 2
  • 17. 9.3 extraction operators (2) ● ->> fetch an array element orobject member as text ● '["a","b","c"]'::json->2 ⟹ c – Instead of "c"
  • 18. 9.3 extraction operators (3) ● #> and #>> fetch data pointed at by a path ● Path is an array of text elements ● Treats arrays correctly by some trying to treat path element as an integer of necessary ● '{"a":[6,7,8]}'::json#>'{a,1}' ⟹ 7 ●
  • 19. 9.3 extraction functions ● json_extract_path(json, VARIADIC path_elems text[]); ● json_extract_path_text(json, VARIADIC path_elems text[]); ● Same as #> and #>> operators, but you can pass the path as a variadic array ● json_extract_path('{"a":[6,7,8]}','a','1') ⟹ 7
  • 20. 9.3 turn JSON into records ● CREATE TYPE x AS (a int, b int); ● SELECT * FROM json_populate_record(null::x, '{"a":1,"b":2}', false); ● SELECT * FROM json_populate_recordset(null::x,'[{"a":1," b":2},{"a":3,"b":4}]', false);
  • 21. 9.3 turn JSON into key/value pairs ● SELECT * FROM json_each('{"a":1,"b":"foo"}') ● SELECT * FROM json_each_text('{"a":1,"b":"foo"}') ● Deliver columns named “key” and “value”
  • 22. 9.3 get keys from JSON object ● SELECT * FROM json_object_keys('{"a":1,"b":"foo"}')
  • 23. 9.3 JSON array processing ● SELECT json_array_length('[1,2,3,4]'); ● SELECT * FROM json_array_elements('[1,2,3,4]')
  • 24. 9.3 the JSON C API ● Need ● A state object ● Some handlers ● Stash these in a JsonSemAction object ● call pg_json_parse()
  • 25. 9.3 API example ● Code can be cloned from https://bitbucket.org/adunstan/json_typeof ● CREATE FUNCTION json_typeof(json) RETURNS text AS 'MODULE_PATHNAME' LANGUAGE C STRICT IMMUTABLE;
  • 26. 9.3 API example state object ● #include <utils/jsonapi.h> ● typedef struct typeof_state { JsonLexContext *lex; JsonTokenType result; } TypeofState;
  • 27. 9.3 API example event handlers ● Need one for each of: ● Array start ● Object start ● Scalar
  • 28. 9.3 API example array/object start handlers ● static void json_typeof_astart (void *state) { TypeofState *_state = (TypeofState *) state; if (_state->lex->lex_level == 0) _state->result = JSON_TOKEN_ARRAY_START; } static void json_typeof_ostart (void *state) { TypeofState *_state = (TypeofState *) state; if (_state->lex->lex_level == 0) _state->result = JSON_TOKEN_OBJECT_START; }
  • 29. 9.3 API example scalar handler ● static void json_typeof_scalar( void *state, char *token, JsonTokenType tokentype) { TypeofState *_state = (TypeofState *) state; if (_state->lex->lex_level == 0) _state->result = tokentype; }
  • 30. 9.3 example function code Datum json_typeof(PG_FUNCTION_ARGS) { text *json = PG_GETARG_TEXT_P(0); TypeofState *state; JsonLexContext *lex = makeJsonLexContext(json, false); JsonSemAction *sem; state = palloc0(sizeof(TypeofState)); sem = palloc0(sizeof(JsonSemAction)); state->lex = lex; sem->semstate = (void *) state; sem->object_start = json_typeof_ostart; sem->array_start = json_typeof_astart; sem->scalar = json_typeof_scalar; pg_parse_json(lex, sem); PG_RETURN_TEXT_P(token_to_type(state->result)); }
  • 31. 9.3 CAPI – what else is it good for? ● Transformations of all kinds ● XML ● YAML ● .... ● An XML transformation was the original working model for creating the API
  • 32. Other useful modules ● Developed for use by my clients ● json_build lets you compose json of arbitrary complexity ● json_object creates a json object from a 1- or 2-dimensional array of text, similar to hstore facility.
  • 33. json_build ● Two functions: ● build_json_object(VARIADIC “any”) ● build_json_array(VARIADIC “any”) ● Together these let you compose deeply nested tree structures safely.
  • 34. json_build example SELECT build_json_object( 'a', build_json_object('b',false,'c',99), 'd', build_json_object('e',array[9,8,7]::int[], 'f', (select row_to_json(r) from ( select relkind, oid::regclass as name from pg_class where relname = 'pg_class') r))); {"a" : {"b" : false, "c" : 99}, "d" : {"e" : [9,8,7], "f" : {"relkind":"r","name":"pg_class"}}}
  • 35. json_object examples SELECT json_object('{a,1,b,2,3,NULL,"d e f","a b c"}'); json_object ------------------------------------------------------- {"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"} -- same but with two dimensions SELECT json_object('{{a,1},{b,2},{3,NULL},{"d e f","a b c"}}'); json_object ------------------------------------------------------- {"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"}
  • 36. json_object examples SELECT json_object('{a,1,b,2,3,NULL,"d e f","a b c"}'); json_object ------------------------------------------------------- {"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"} -- same but with two dimensions SELECT json_object('{{a,1},{b,2},{3,NULL},{"d e f","a b c"}}'); json_object ------------------------------------------------------- {"a" : "1", "b" : "2", "3" : null, "d e f" : "a b c"}
  • 37. Extension repos ● https://github.com/pgexperts/json_build ● https://bitbucket.org/qooleot/json_object ● Also on PGXN
  • 38. Future of JSON in PostgreSQL ● Possible binary representation ● Avoid reparsing ● Could be vastly faster for some operations ● Should we use a dictionary and store structure separately? ● General document store ● Need to get around the “rewrite a whole datum” issue
  • 39. Credit ● 9.3 core development work sponsored by Heroku ● Other work sponsored by PGExperts clients and IVC