PostgreSQL Training Topic-Wise Online Mock Tests & Free MCQ Practice
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PostgreSQL Training — Topic-Wise Mock Tests
Expand any module below to start a live timed MCQ exam across 244 Mock Test sets (max 2 free attempts per topic per day).
All Modules & Topics in PostgreSQL Training
PostgreSQL 17 Architecture — Object-Relational Engine, 8 KB Pages, WAL & MVCC Snapshot Isolation
Purpose: To understand and apply PostgreSQL 17 Architecture — Object-Relational Engine, 8 KB Pages, WAL & MVCC Snapshot Isolation in real PostgreSQL systems — specifically: How PostgreSQL achieves strict ACID compliance using Write-Ahead Logging (WAL), 8 KB slotted heap pages, `shared_buffers`, and `xmin`/`xmax` MVCC tuple snapshots, so your code stays reliable, fast, and easy to maintain in production.
Advantages of PostgreSQL — Transactional DDL, Partial/GIN Indexes, Rich Types & Extensions
Purpose: To understand and apply Advantages of PostgreSQL — Transactional DDL, Partial/GIN Indexes, Rich Types & Extensions in real PostgreSQL systems — specifically: Why PostgreSQL leads modern engineering stacks: atomic Transactional DDL (`BEGIN ... ALTER TABLE ... ROLLBACK`), Partial & Expression indexes, `JSONB`, `pgvector`, and BSD/PostgreSQL open licensing, so your code stays reliable, fast, and easy to maintain in production.
Installing & Tuning PostgreSQL 17 — `initdb --data-checksums`, `$PGDATA` & `postgresql.conf`
Purpose: To understand and apply Installing & Tuning PostgreSQL 17 — `initdb --data-checksums`, `$PGDATA` & `postgresql.conf` in real PostgreSQL systems — specifically: Provisioning PostgreSQL 17 with hardware page checksums (`--data-checksums`) and sizing `shared_buffers` (~25% RAM), `work_mem`, and `wal_level = replica`, so your code stays reliable, fast, and easy to maintain in production.
Connecting to PostgreSQL — Port 5432, `pg_hba.conf` (`scram-sha-256`), TLS & PgBouncer Pooling
Purpose: To understand and apply Connecting to PostgreSQL — Port 5432, `pg_hba.conf` (`scram-sha-256`), TLS & PgBouncer Pooling in real PostgreSQL systems — specifically: Securing TCP/Unix-socket connections via `pg_hba.conf` (`hostssl ... scram-sha-256`), `psql` connection URIs, `sslmode=verify-full`, and PgBouncer process-per-connection pooling, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL SQL Syntax — Unquoted Lowercase Folding, Single vs Double Quotes, `$$` & Clause Order
Purpose: To understand and apply PostgreSQL SQL Syntax — Unquoted Lowercase Folding, Single vs Double Quotes, `$$` & Clause Order in real PostgreSQL systems — specifically: Mastering PostgreSQL’s strict ANSI lexical rules: unquoted identifiers fold to lowercase (`UserID` -> `userid`), `'single quotes'` denote values, `"double quotes"` denote identifiers, and `$$` avoids backslash/quote escaping, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `CREATE DATABASE` — `template0` vs `template1`, `UTF8` ICU Collations & Cross-DB Isolation
Purpose: To understand and apply PostgreSQL `CREATE DATABASE` — `template0` vs `template1`, `UTF8` ICU Collations & Cross-DB Isolation in real PostgreSQL systems — specifically: Creating physically isolated databases inside a PostgreSQL cluster (`OWNER`, `ENCODING 'UTF8'`, `TEMPLATE template0`, `LOCALE_PROVIDER icu`, `CONNECTION LIMIT`, and PG 13+ `DROP DATABASE ... WITH (FORCE)`), so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL Schemas & `search_path` — Namespace Resolution, PG 15+ `public` Hardening & Multi-Tenancy
Purpose: To understand and apply PostgreSQL Schemas & `search_path` — Namespace Resolution, PG 15+ `public` Hardening & Multi-Tenancy in real PostgreSQL systems — specifically: How `Cluster -> Database -> Schema -> Table` hierarchy allows cross-schema Foreign Keys and joins while `search_path` controls unqualified table/function resolution, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `CREATE SCHEMA` — `AUTHORIZATION`, Inline Atomic DDL & Default Privileges
Purpose: To understand and apply PostgreSQL `CREATE SCHEMA` — `AUTHORIZATION`, Inline Atomic DDL & Default Privileges in real PostgreSQL systems — specifically: Provisioning role-owned schemas (`CREATE SCHEMA IF NOT EXISTS analytics AUTHORIZATION analytics_owner`) and configuring `ALTER DEFAULT PRIVILEGES` for read-only reporting roles, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL Data Types Overview — Rich Native Types (`inet`, Ranges, Arrays), Casting (`::`) & Column Alignment
Purpose: To understand and apply PostgreSQL Data Types Overview — Rich Native Types (`inet`, Ranges, Arrays), Casting (`::`) & Column Alignment in real PostgreSQL systems — specifically: Choosing expressive self-validating PostgreSQL types (`inet` IP subnets, `tstzrange` exclusion constraints, `pg_typeof()`, `CAST` / `::`) and minimizing 8-byte struct alignment padding, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `NUMERIC` / `DECIMAL` — Exact Base-10 Arithmetic vs IEEE-754 Float Drift, Scale & `NaN`
Purpose: To understand and apply PostgreSQL `NUMERIC` / `DECIMAL` — Exact Base-10 Arithmetic vs IEEE-754 Float Drift, Scale & `NaN` in real PostgreSQL systems — specifically: Why financial ledgers, tax engines, and token balances require exact `NUMERIC(precision, scale)` (synonym `DECIMAL`) over inexact binary `DOUBLE PRECISION` (`0.1::float8 + 0.2::float8 <> 0.3`), so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `VARCHAR(n)` vs `CHAR(n)` vs `TEXT` — `varlena` Internals, Character Count & Zero-Lock Limits
Purpose: To understand and apply PostgreSQL `VARCHAR(n)` vs `CHAR(n)` vs `TEXT` — `varlena` Internals, Character Count & Zero-Lock Limits in real PostgreSQL systems — specifically: Why PostgreSQL stores `VARCHAR(n)`, `VARCHAR`, and `TEXT` using the exact same `varlena` C structure (counting Unicode characters, not bytes!), and why `CHAR(n)` wastes space with trailing spaces, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `BOOLEAN` — 1-Byte Storage, Three-Valued Logic (`TRUE`/`FALSE`/`NULL`) & `IS DISTINCT FROM`
Purpose: To understand and apply PostgreSQL `BOOLEAN` — 1-Byte Storage, Three-Valued Logic (`TRUE`/`FALSE`/`NULL`) & `IS DISTINCT FROM` in real PostgreSQL systems — specifically: Mastering 1-byte SQL `BOOLEAN` columns, `FILTER (WHERE ...)` aggregates, and avoiding silent data-loss bugs from `NULL` in `<>`, `=`, and `NOT IN` clauses, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `BIGINT` (`int8`) — 64-Bit Range, Preventing `2.14B` `INT4` Exhaustion & FK Type Matching
Purpose: To understand and apply PostgreSQL `BIGINT` (`int8`) — 64-Bit Range, Preventing `2.14B` `INT4` Exhaustion & FK Type Matching in real PostgreSQL systems — specifically: Why high-growth events, logs, and primary keys standardize on 8-byte signed `BIGINT` (`-9.22e18` to `+9.22e18`) to eliminate catastrophic 32-bit `INTEGER` (`2,147,483,647`) exhaustion, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `SERIAL` vs `GENERATED ALWAYS AS IDENTITY` — Sequence Mechanics, Gaps & `setval` Desync
Purpose: To understand and apply PostgreSQL `SERIAL` vs `GENERATED ALWAYS AS IDENTITY` — Sequence Mechanics, Gaps & `setval` Desync in real PostgreSQL systems — specifically: Understanding how legacy `SERIAL` expands into `INTEGER + CREATE SEQUENCE + DEFAULT nextval(...)`, why explicit ID inserts desync `SERIAL` sequences, and why PostgreSQL 10+ recommends `GENERATED ALWAYS AS IDENTITY`, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `TIMESTAMPTZ` vs `TIMESTAMP` — 8-Byte UTC Microseconds, `AT TIME ZONE` & SARGable Ranges
Purpose: To understand and apply PostgreSQL `TIMESTAMPTZ` vs `TIMESTAMP` — 8-Byte UTC Microseconds, `AT TIME ZONE` & SARGable Ranges in real PostgreSQL systems — specifically: Why PostgreSQL’s “Don’t Do This” wiki explicitly warns against naive `TIMESTAMP` (`without time zone`): `TIMESTAMPTZ` takes the exact same 8 bytes, stores pure UTC, and formats per session `TimeZone`, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `INTERVAL` — 16-Byte Calendar/Day/Microsecond Triplet, DST Awareness & `justify_interval`
Purpose: To understand and apply PostgreSQL `INTERVAL` — 16-Byte Calendar/Day/Microsecond Triplet, DST Awareness & `justify_interval` in real PostgreSQL systems — specifically: Performing precise SLA, retention, and billing-cycle date math using PostgreSQL’s 16-byte `INTERVAL` (`months` + `days` + `microseconds`), `AGE()`, `EXTRACT(EPOCH FROM ...)`, and `make_interval()`, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `UUID` — 16-Byte Binary Storage, `gen_random_uuid()`, & `UUIDv4` B-Tree Fragmentation vs `UUIDv7`
Purpose: To understand and apply PostgreSQL `UUID` — 16-Byte Binary Storage, `gen_random_uuid()`, & `UUIDv4` B-Tree Fragmentation vs `UUIDv7` in real PostgreSQL systems — specifically: Generating collision-free distributed identifiers without leaking sequential row counts, storing them in 16 binary bytes (not 36 ASCII chars), and avoiding random `UUIDv4` B-Tree page-split write amplification on massive tables, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `JSON` vs `JSONB` — Decomposed Binary Storage, `->` vs `->>`, Containment `@>` & GIN Indexes
Purpose: To understand and apply PostgreSQL `JSON` vs `JSONB` — Decomposed Binary Storage, `->` vs `->>`, Containment `@>` & GIN Indexes in real PostgreSQL systems — specifically: Combining relational ACID rigor with schemaless flexibility using binary `JSONB`, containment (`@>`), key-existence (`?`), `jsonb_set()`, SQL/JSON path (`@?`), and `GIN (col jsonb_path_ops)` indexing, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `TEXT` — TOAST Internals (`lz4` Compression, Out-of-Line Chunks), `SELECT *` Cost & Full-Text Search
Purpose: To understand and apply PostgreSQL `TEXT` — TOAST Internals (`lz4` Compression, Out-of-Line Chunks), `SELECT *` Cost & Full-Text Search in real PostgreSQL systems — specifically: How PostgreSQL stores `TEXT` strings up to 1 GB transparently across 8 KB heap pages via TOAST (`COMPRESSION lz4`), why `SELECT id, title` avoids detoasting out-of-line chunks, and indexing text via `tsvector` / `pg_trgm`, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL `ALTER SCHEMA` — `RENAME TO`, `OWNER TO`, OID Dependency Tracking & Zero-Downtime Cutovers
Purpose: To understand and apply PostgreSQL `ALTER SCHEMA` — `RENAME TO`, `OWNER TO`, OID Dependency Tracking & Zero-Downtime Cutovers in real PostgreSQL systems — specifically: Managing schema lifecycle changes (`ALTER SCHEMA staging RENAME TO v2_live; ALTER SCHEMA v2_live OWNER TO ...`) safely inside atomic transactions while understanding catalog OID binding vs string-based client references, so your code stays reliable, fast, and easy to maintain in production.
Tuple Visibility (xmin/xmax), Dead Tuples, HOT Updates & Table Bloat
Purpose: To understand and apply Tuple Visibility (xmin/xmax), Dead Tuples, HOT Updates & Table Bloat in real PostgreSQL systems — specifically: Design update patterns and fillfactor settings that keep PostgreSQL heaps lean and fast, so your code stays reliable, fast, and easy to maintain in production.
Tuning Per-Table Autovacuum & Preventing Transaction ID Wraparound
Purpose: To understand and apply Tuning Per-Table Autovacuum & Preventing Transaction ID Wraparound in real PostgreSQL systems — specifically: Ensure high-churn queue/session tables vacuum continuously without emergency downtime, so your code stays reliable, fast, and easy to maintain in production.
Lock Modes, lock_timeout Guards & Zero-Downtime DDL Habits
Purpose: To understand and apply Lock Modes, lock_timeout Guards & Zero-Downtime DDL Habits in real PostgreSQL systems — specifically: Add columns, NOT NULL check constraints, and CREATE INDEX CONCURRENTLY without locking traffic!, so your code stays reliable, fast, and easy to maintain in production.
SKIP LOCKED Transactional Queues & Advisory Locks
Purpose: To understand and apply SKIP LOCKED Transactional Queues & Advisory Locks in real PostgreSQL systems — specifically: Build rock-solid concurrent job claimers right inside PostgreSQL, so your code stays reliable, fast, and easy to maintain in production.
Reading EXPLAIN (ANALYZE, BUFFERS): Seq/Bitmap/Index-Only Scans & Sort Spills
Purpose: To understand and apply Reading EXPLAIN (ANALYZE, BUFFERS): Seq/Bitmap/Index-Only Scans & Sort Spills in real PostgreSQL systems — specifically: Spot disk work_mem spills and stale statistics immediately from execution plans, so your code stays reliable, fast, and easy to maintain in production.
Partial Indexes, Expression Indexes & Covering INCLUDE Columns
Purpose: To understand and apply Partial Indexes, Expression Indexes & Covering INCLUDE Columns in real PostgreSQL systems — specifically: Index only the 2% active unpaid orders for tiny RAM-resident sub-millisecond lookups, so your code stays reliable, fast, and easy to maintain in production.
JSONB Containment (@>), jsonb_path_ops GIN Indexes & Full-Text tsvector
Purpose: To understand and apply JSONB Containment (@>), jsonb_path_ops GIN Indexes & Full-Text tsvector in real PostgreSQL systems — specifically: Query flexible attributes and ranked full-text search without adding separate search infra, so your code stays reliable, fast, and easy to maintain in production.
BRIN Indexes for Billion-Row Append-Only Logs & pg_stat_statements Audits
Purpose: To understand and apply BRIN Indexes for Billion-Row Append-Only Logs & pg_stat_statements Audits in real PostgreSQL systems — specifically: Rank the top 10 DB CPU-consuming queries in production and fix them systematically, so your code stays reliable, fast, and easy to maintain in production.
Declarative Range/Hash Partitioning, Partition Pruning & Instant Detach
Purpose: To understand and apply Declarative Range/Hash Partitioning, Partition Pruning & Instant Detach in real PostgreSQL systems — specifically: Manage 500GB+ time-series tables cleanly and drop old monthly partitions in 5ms, so your code stays reliable, fast, and easy to maintain in production.
Multi-Tenant Row-Level Security (RLS) Policies with Session Context
Purpose: To understand and apply Multi-Tenant Row-Level Security (RLS) Policies with Session Context in real PostgreSQL systems — specifically: Enforce tenant isolation inside the PostgreSQL kernel so app bugs never leak cross-tenant rows!, so your code stays reliable, fast, and easy to maintain in production.
Lateral Joins, Grouping Sets, Window Frames & PL/pgSQL Audit Triggers
Purpose: To understand and apply Lateral Joins, Grouping Sets, Window Frames & PL/pgSQL Audit Triggers in real PostgreSQL systems — specifically: Compute rich analytical rollups and tamper-evident compliance audit trails, so your code stays reliable, fast, and easy to maintain in production.
pgvector Embeddings, HNSW Indexes & Hybrid Relational + Semantic Queries
Purpose: To understand and apply pgvector Embeddings, HNSW Indexes & Hybrid Relational + Semantic Queries in real PostgreSQL systems — specifically: Power modern AI RAG retrieval directly inside ACID PostgreSQL transactions, so your code stays reliable, fast, and easy to maintain in production.
Transaction-Mode Connection Pooling with PgBouncer
Purpose: To understand and apply Transaction-Mode Connection Pooling with PgBouncer in real PostgreSQL systems — specifically: Multiplex 2,000 microservice pods smoothly onto 80 physical PostgreSQL backend processes, so your code stays reliable, fast, and easy to maintain in production.
Physical Streaming Replication, Replication Slots & Logical CDC
Purpose: To understand and apply Physical Streaming Replication, Replication Slots & Logical CDC in real PostgreSQL systems — specifically: Scale read replicas safely while monitoring slot lag to prevent WAL disk overflow, so your code stays reliable, fast, and easy to maintain in production.
Continuous WAL Archiving (pgBackRest) & Point-in-Time Recovery (PITR)
Purpose: To understand and apply Continuous WAL Archiving (pgBackRest) & Point-in-Time Recovery (PITR) in real PostgreSQL systems — specifically: Practice restoring a corrupted cluster to 14:32:10 UTC with verified integrity, so your code stays reliable, fast, and easy to maintain in production.
SCRAM-SHA-256, SSL Enforcement, Role Hierarchies & Patroni HA Failover
Purpose: To understand and apply SCRAM-SHA-256, SSL Enforcement, Role Hierarchies & Patroni HA Failover in real PostgreSQL systems — specifically: Automate sub-15-second primary failover and pass enterprise DB security audits, so your code stays reliable, fast, and easy to maintain in production.
MVCC Tuple Visibility, Dead Tuples, Autovacuum Tuning & Transaction ID Wraparound Safety
Purpose: To understand and apply MVCC Tuple Visibility, Dead Tuples, Autovacuum Tuning & Transaction ID Wraparound Safety in real PostgreSQL systems — specifically: Keep high-write PostgreSQL tables free from table/index bloat and vacuum stalls, so your code stays reliable, fast, and easy to maintain in production.
PostgreSQL Row-Level Security (RLS) Policies & Zero-Downtime CREATE INDEX CONCURRENTLY
Purpose: To understand and apply PostgreSQL Row-Level Security (RLS) Policies & Zero-Downtime CREATE INDEX CONCURRENTLY in real PostgreSQL systems — specifically: Enforce tenant isolation directly inside Postgres and evolve live schemas without write locks, so your code stays reliable, fast, and easy to maintain in production.
Declarative Range/Hash Partitioning, pg_stat_statements & Connection Pooling (PgBouncer)
Purpose: To understand and apply Declarative Range/Hash Partitioning, pg_stat_statements & Connection Pooling (PgBouncer) in real PostgreSQL systems — specifically: Scale to thousands of concurrent app connections and isolate slow queries scientifically, so your code stays reliable, fast, and easy to maintain in production.
Full-Text Search (tsvector / GIN) + pgvector HNSW Embeddings for AI/RAG Workloads
Purpose: To understand and apply Full-Text Search (tsvector / GIN) + pgvector HNSW Embeddings for AI/RAG Workloads in real PostgreSQL systems — specifically: Run relational transactions, keyword search, and vector similarity inside a single ACID database, so your code stays reliable, fast, and easy to maintain in production.
Streaming & Logical Replication, WAL Archiving & Point-in-Time Recovery (PITR)
Purpose: To understand and apply Streaming & Logical Replication, WAL Archiving & Point-in-Time Recovery (PITR) in real PostgreSQL systems — specifically: Execute zero-data-loss failover drills and major-version upgrades with minimal downtime, so your code stays reliable, fast, and easy to maintain in production.
Reading Complex EXPLAIN (ANALYZE, BUFFERS) Plans & Postgres Interview Scenarios
Purpose: To understand and apply Reading Complex EXPLAIN (ANALYZE, BUFFERS) Plans & Postgres Interview Scenarios in real PostgreSQL systems — specifically: Diagnose Nested Loop vs Hash Join misestimates, spill-to-disk sorts, and lock queues, so your code stays reliable, fast, and easy to maintain in production.
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