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PostgreSQL Deep Dive

Data SystemsRelational DatabasesđŸŸĸ Free Lesson

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Data Systems

PostgreSQL Deep Dive

PostgreSQL is the most advanced open-source relational database. Master its advanced features: JSONB, partitioning, full-text search, CTEs, window functions, and extension ecosystem.

  • Extensibility — Custom types, functions, and extensions
  • Standards Compliance — Full SQL standard support
  • Advanced Features — Window functions, CTEs, JSONB, geospatial

PostgreSQL is the database that grows with you.

PostgreSQL Architecture

Process Architecture

ClientPostmasterConnection handling, process managementBackend 1Query executionPlan + ExecuteBuffer accessBackend 2Query executionPlan + ExecuteBuffer accessShared MemoryShared BuffersWAL BuffersLock TableBackgroundCheckpointerWriterWAL WriterAutovacuum

Advanced SQL Features

Window Functions

FunctionPurposeExample
ROW_NUMBER()Sequential numberingRank rows within a partition
RANK()Ranking with gapsTies get same rank
DENSE_RANK()Ranking without gapsNo gaps after ties
LAG/LEAD()Access previous/next rowsCompare with adjacent rows
SUM/AVG() OVERRunning aggregatesRunning total, moving average
NTILE()Divide into bucketsQuartiles, deciles

JSONB

OperatorDescriptionExample
->Get JSON fielddata->'name'
->>Get JSON field as textdata->>'name'
#>Get JSON pathdata#>'{address,city}'
@>Containsdata @> '{"status":"active"}'
?Key existsdata ? 'name'
jsonb_path_querySQL/JSON pathjsonb_path_query(data, '$.orders[*].price')

Table Partitioning

Partition TypeStrategyUse Case
RangeValue ranges (e.g., dates)Time-series data
ListDiscrete values (e.g., regions)Multi-tenant systems
HashHash of partition keyEven distribution

Extension Ecosystem

ExtensionPurpose
PostGISGeospatial data and queries
TimescaleDBTime-series data optimization
pgvectorVector similarity search (AI/ML)
pg_trgmTrigram similarity for fuzzy search
uuid-osspUUID generation
pg_stat_statementsQuery performance analysis

Practice Exercises

  1. Window Functions: Write a SQL query to calculate the 7-day moving average of daily revenue, including day-over-day percentage change.

  2. JSONB Design: Design a PostgreSQL schema for an e-commerce order system using JSONB for flexible product attributes. What indexes would you create?

  3. Partitioning Strategy: Design the partitioning strategy for a logging table that receives 10M rows per day and needs to retain 1 year of data.

  4. Performance Analysis: Given a slow query, write the steps you would take to diagnose and optimize it using EXPLAIN ANALYZE, pg_stat_statements, and index analysis.


What to Learn Next

-> SQL Deep Dive PostgreSQL, MySQL, indexing strategies, and query optimization.

-> MongoDB Deep Dive Advanced MongoDB features, aggregation pipeline, and sharding.

-> Spanner and CockroachDB Deep dive into specific NewSQL implementations.

-> Database Indexing B-trees, hash indexes, and indexing strategies.

-> Data Partitioning Sharding strategies, consistent hashing, and partition keys.

-> Data Replication Sync vs async replication, leader election, and consistency.

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