cassandra

name	cassandra
description	Cassandra — partition keys, CQL, consistency levels, CLI.

Cassandra Reference

When to Load

Load when the project uses Cassandra or ScyllaDB (signal: cassandra-driver, cassandra-python-driver, datastax-astra, cassandra: in docker-compose, CASSANDRA_HOST env var).

CLI Connection

# cqlsh (bundled with Cassandra):
cqlsh "$CASSANDRA_HOST" "${CASSANDRA_PORT:-9042}" \
  -u "$CASSANDRA_USER" -p "$CASSANDRA_PASSWORD"

# with TLS:
cqlsh "$CASSANDRA_HOST" 9142 --ssl \
  -u "$CASSANDRA_USER" -p "$CASSANDRA_PASSWORD"

# DataStax Astra (cloud):
cqlsh -b "$ASTRA_BUNDLE_PATH" -u "$ASTRA_CLIENT_ID" -p "$ASTRA_SECRET"

Key inspection commands:

DESCRIBE KEYSPACES;
DESCRIBE TABLES;
DESCRIBE TABLE keyspace.table;
SELECT * FROM system.local;               -- node info, rack, DC
SELECT * FROM system.peers;              -- cluster topology
TRACING ON;                              -- trace next query for latency breakdown

Data Model — Think in Queries

Cassandra requires query-driven data modeling. Unlike relational databases, denormalization is expected.

Primary key anatomy:

PRIMARY KEY ((partition_key), clustering_col1, clustering_col2)

• Partition key: determines which node holds the data; must appear in every query (WHERE partition_key = ?)
• Clustering columns: physical sort order within the partition; enable range queries
• All data within a partition is stored together; partitions should stay under ~100 MB

Design rules:

1. Know your queries before designing the table
2. One table per query pattern is normal
3. Avoid large partitions (millions of rows in one partition → hotspot)
4. Avoid unbounded clustering columns — add a time-bucket to partition key if inserting time series

CQL Essentials

-- Create table with TTL:
CREATE TABLE user_sessions (
  user_id   UUID,
  session_id UUID,
  data      TEXT,
  PRIMARY KEY (user_id, session_id)
) WITH default_time_to_live = 86400;

-- Insert with per-row TTL:
INSERT INTO user_sessions (user_id, session_id, data)
VALUES (?, ?, ?) USING TTL 3600;

-- Lightweight transaction (compare-and-set):
INSERT INTO users (id, email) VALUES (?, ?) IF NOT EXISTS;
UPDATE users SET email = ? WHERE id = ? IF email = ?;

Consistency Levels

Level	Reads from	Writes to	Trade-off
ONE	1 replica	1 replica	Fastest; risk of stale reads
QUORUM	Majority	Majority	Strong consistency across DC
LOCAL_QUORUM	Majority in local DC	Majority in local DC	Low latency in multi-DC
ALL	All replicas	All replicas	Strongest; not fault-tolerant
EACH_QUORUM	Quorum per DC	Quorum per DC	Geo-distributed writes

Strong consistency rule: read CL + write CL > replication factor

• RF=3, write QUORUM (2) + read QUORUM (2) = 4 > 3 → strongly consistent

Default recommendation: write LOCAL_QUORUM, read LOCAL_QUORUM for most OLTP workloads.

Compaction Strategies

Strategy	Best for
SizeTieredCompactionStrategy (default)	Write-heavy; infrequent reads; heavy data
LeveledCompactionStrategy	Read-heavy; predictable read latency; smaller SSTables
TimeWindowCompactionStrategy	Time series with TTL; groups SSTables by time window

Change strategy: ALTER TABLE t WITH compaction = {'class': 'LeveledCompactionStrategy'};

Secondary Indexes & Materialized Views

• Secondary indexes: avoid on high-cardinality columns or on columns used without the partition key — causes scatter reads across all nodes
• Materialized Views: maintained by Cassandra; trades write overhead for read convenience; use carefully (risk of write amplification and consistency lag)
• SAI (Storage-Attached Index): Cassandra 4.x / DataStax; column-level index without full-table scatter; prefer over legacy secondary indexes

Tombstones & Deletion

• Deletes write a tombstone (not an immediate removal); tombstones are removed during compaction
• Excessive tombstones (> 100k per read) cause read timeouts — monitor with nodetool tpstats
• Use TTL instead of explicit deletes for time-expiring data
• Never issue TRUNCATE in production without checking dependent materialized views

Common Gotchas

Gotcha	Fix
ALLOW FILTERING in query	Re-model the table for the query or add a SAI index
Hotspot partition (one partition grows unbounded)	Add a time-bucket to the partition key
Lightweight transactions (IF NOT EXISTS) slow	Use sparingly — they use Paxos; not for hot paths
Reading with IN on partition key	May cause coordinator hotspot; prefer parallel single-partition reads
nodetool repair not scheduled	Run weekly on each node; skipping causes inconsistency and tombstone accumulation