storage: long term cache for integer-like PK column in memory

[Lloyd-Pottiger]

What problem does this PR solve?

Issue Number: ref #9032

Problem Summary:

What is changed and how it works?

Optimize for VectorDBBench.

• Cache PK data in memory for queries. Max cache size is 500MB. This avoids IO & decompress repeatedly.
• Optimize ColumnArray::insertManyDefaults. It is a critical path used in Vector Search, because Vector Search will return sparse results. (TODO: Use ColumnSparse is better)
• Fix a mistake that previously we build a useless debug string String block_filter_value;, which costs time.
• Optimize the return filter in Vector Search. Flamegraph shows that BitmapFilter.get() takes time. So this PR totally drops it. DMFileWithVectorIndexBlockInputStream now builds the return filter directly from the result rows.

Benchmark (VectorDBBench, Cohere 1M vectors, 768 dimensions):

Before this PR @ Macbook M1 Pro: 180QPS @ 30 concurrency

After this PR @ Macbook M1 Pro: 250QPS @ 30 concurrency

storage: cache PK column in memory

Check List

Tests

• Unit test
• Integration test
• Manual test (add detailed scripts or steps below)
• No code

Side effects

• Performance regression: Consumes more CPU
• Performance regression: Consumes more Memory
• Breaking backward compatibility

Documentation

• Affects user behaviors
• Contains syntax changes
• Contains variable changes
• Contains experimental features
• Changes MySQL compatibility

Release note

None

[CalvinNeo]

Wow, so it is supported now

[CalvinNeo]

lgtm

[ti-chi-bot]

[APPROVALNOTIFIER] This PR is APPROVED

This pull-request has been approved by: breezewish, CalvinNeo

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[ti-chi-bot]

[LGTM Timeline notifier]

Timeline:

• 2024-09-20 07:29:41.099539626 +0000 UTC m=+1205450.839963562: ☑️ agreed by CalvinNeo.
• 2024-09-21 06:31:53.791462941 +0000 UTC m=+1288383.531886882: ☑️ agreed by breezewish.

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