starrocks-bucketing

What problem does it solve?

This skill helps you choose StarRocks table bucketing (distribution) so data is evenly spread across backends, joins can use colocate when appropriate, and performance does not degrade due to skew or poorly sized tablets.

Core Features & Use Cases

• Design bucketing strategy: pick DISTRIBUTED BY HASH vs DISTRIBUTED BY RANDOM, select distribution keys, and choose an appropriate bucket count.
• Tune for tablet sizing: target 1–10 GB per tablet (recommended ~5 GB) to balance parallelism and metadata/compaction overhead.
• Diagnose and fix skew: measure tablet distribution and skew ratios, identify skew drivers, and adjust distribution keys or switch strategy.
• Enable colocate joins: configure colocate_with consistently so frequently joined tables avoid shuffle and use local (colocate) joins.
• Evolve bucket counts safely: apply ALTER TABLE ... DISTRIBUTED BY ... BUCKETS ... when data volume or cluster size changes.

Quick Start

Use the starrocks-bucketing skill to design your StarRocks table distribution by selecting the right distribution key, bucket count, and colocate join settings for your expected data size and join patterns.