Alexey Scherbakov created IGNITE-22977:
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Summary: Reduce latency for txn preparing phase
Key: IGNITE-22977
URL: https://issues.apache.org/jira/browse/IGNITE-22977
Project: Ignite
Issue Type: Improvement
Affects Versions: 3.0
Reporter: Alexey Scherbakov
Tx mapping phase has some deficiencies, discovered during tracing.
# HybridClockImpl uses currentTimeMillis on each update. This call is heavy,
better use FastTimestamps with 1 millisecond resolution.
# CompletableFuture has unexpected latency issues:
## onTimeout add 4-5 us of latency
## chaining adds 0.5-1 us of latency. instead of using
CompletableFuture.completedFuture(val).handle(closure) better to use if
(fut.isDone()) closure();
# Metadata validation {{{}validateTableExistence{}}},
{{{}validateSchemaMatch{}}}, {{{}waitForSchemasBeforeReading{}}}should wait
only once.
# Number of shared memory access (like updating some counter) should be
reduced. For example tx counting should be only during index rebuild.
# BinaryRow generation is 2x slower than BinaryObject in AI2: 5us vs 10us
(known issue, just for clarity)
# Thread switching brings a lot of latency (known issue, just for clarity).
Can try green threads pool to mitigate this (requires java 21).
# RAFT command is completed always in partitions thread pool
# Number of {{clockService.now()}} calls should be reduced.
# Each tx lock cost 2us. Might be improved to 1us.
# Lease checking adds waiter even if not necessary.
# Row id generation uses randomUUID which is heavy.
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