JSONB Tricks: Operators, Indexes, and When (Not) to Use It | PostgresOpen 2019 | Colton Shepard

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The document discusses the use of JSON and JSONB data types in PostgreSQL, highlighting their characteristics such as being human-readable and indexable. It describes various operators and functions introduced in PostgreSQL 12 for querying JSON data, including jsonb_path_query and operators like @ and #>. The document also includes links to customer stories and resources for further learning about the use of JSON in PostgreSQL.

Technology

What is all this, anyways?
JavaScript Object Notation Data Interchange Format
RFC 7158
Human readable lightweight data format
One of 2 Postgres JSON data types.
Decomposed for storage, not stored as string
• Fast and indexable
• High disk usage

Good use cases
Entity–attribute–value model tables

Less Good Use Cases: Statistics Gathering Issues

Customer Story: Heap Analytics
https://heap.io/blog/engineering/when-to-avoid-jsonb-in-a-postgresql-schema

The ? operator
Does this string exist as a top-level key within the JSON value?

The ? operator
What about this array of strings?

Special mention: GIN function index with gin_trgm_ops

$Postgres 12 New datatype: jsonpath Provides a binary representation of the parsed SQL/JSON path expression 1. .key returns object member with specified key 2. .* returns all object members at current level 3. .** returns all object members at current level and below 4. .**{level} or .**{start_level to end_level} returns all at specified level(s) 5. [subscript, ...] returns the value at specified array location https://www.postgresql.org/docs/devel/datatype-json.html#DATATYPE-JSONPATH$

Postgres 12: The jsonb_path_query operator

Postgres 12: jsonb_path_query with .* and .**

$Postgres 12: jsonb_path_query with .**{level}$

Postgres 12: jsonb_path_query with arrays

Postgres 12: the jsonb_path_exists operator
Gives bool indicating whether the path exists.

Postgres 12: the jsonb_path_match operator
This allows for any logic that’ll output Boolean results

Postgres 12: the jsonb_path_query_array operator
Much like jsonb_path_query, but you get an array instead:

Postgres 12: the jsonb_path_query_first operator
Get first matching result:

General resources to
learn more
https://www.youtube.com/watch?v=AeMaBwd90SI
https://heap.io/blog/engineering/when-to-avoid-jsonb-in-a-
postgresql-schema
https://bitnine.net/blog-postgresql/postgresql-internals-jsonb-
type-and-its-indexes/
https://www.citusdata.com/blog/2016/07/14/choosing-nosql-
hstore-json-jsonb/
https://www.postgresql.org/docs/12/functions-
json.html#FUNCTIONS-SQLJSON-PATH
https://paquier.xyz/postgresql-2/postgres-12-jsonpath/
https://www.citusdata.com/blog/2016/07/25/sharding-json-in-
postgres-and-performance/

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The document discusses common issues and troubleshooting strategies related to PostgreSQL databases, particularly from the perspective of application developers. It emphasizes understanding system resource allocation, workload management, and potential bottlenecks while offering tools for diagnosing problems. The talk also references resilience in complex systems and the importance of recognizing various sources of database performance issues.

Why PostgreSQL Why This Database Why Now | Nordic PGDay 2019 | Claire GiordanoCitus Data

The presentation at Nordic PGDay 2019 in Copenhagen, led by Claire Giordano from Citus Data/Microsoft, discusses the appeal of PostgreSQL as a database choice. It highlights the community support, performance growth, and features such as JSONB and extensions that contribute to its increasing popularity. The session emphasizes PostgreSQL's ability to meet modern data requirements and its strong ecosystem.

Scaling Multi-Tenant Applications Using the Django ORM & Postgres | PyCaribbe...Citus Data

The document explores scaling multi-tenant applications using Django ORM and PostgreSQL, defining multi-tenancy and offering three solutions: one database per tenant, one schema per tenant, and shared tables architecture. It emphasizes the benefits and drawbacks of each approach, particularly focusing on the implementation of shared tables with Django-Multitenant for efficient tenant isolation. Additionally, it highlights the advantages of using PostgreSQL and the Citus extension for distributed architecture to enhance scalability.