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Documentation Index

Fetch the complete documentation index at: https://docs.automq.com/llms.txt

Use this file to discover all available pages before exploring further.

AutoMQ enhances server performance through methods like read/write efficiency optimization and resource isolation, ensuring stable and efficient operation.
Users should adjust parameters based on their hardware environment and business scenarios.

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s3.stream.allocator.policy

Configure the memory allocation strategy for AutoMQ by selecting either POOLED_HEAP or POOLED_DIRECT. If memory resources are abundant (> 8 GiB), it is advisable to use POOLED_DIRECT to alleviate GC pressure.

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s3.wal.cache.size

Manage the size of the Log Cache, which influences the maximum size of cached data during Tail Read (hot reads).

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s3.block.cache.size

Control the size of the Block Cache; it influences the maximum size of data cached during Catch-up Read (catch-up read, cold read). In Catch-up Read scenarios, consider appropriately increasing this value.

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s3.wal.upload.threshold

Manage the amount of data AutoMQ accumulates in the Log Cache before triggering an S3 upload. It is advisable not to exceed 1/3 of s3.wal.cache.size. When the memory allocation strategy is POOLED_HEAP, the sum of s3.wal.cache.size and s3.block.cache.size should be approximately 1/4 of MaxHeapSize. When the memory allocation strategy is POOLED_DIRECT, the sum of s3.wal.cache.size and s3.block.cache.size should be about 1/2 of MaxDirectMemorySize (if MaxDirectMemorySize is large, it can be slightly increased).
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Small
Medium
Large
Physical Memory
8 GiB
16 GiB
32 GiB
s3.stream.allocator.policy
POOLED_HEAP
POOLED_DIRECT
POOLED_DIRECT
-XX:MaxHeapSize
6g
6g
12g
-XX:MaxDirectMemorySize
-
6g
14g
s3.wal.cache.size
1,073,741,824
2,147,483,648
6,442,450,944
s3.block.cache.size
536,870,912
1,073,741,824
4,294,967,296
s3.wal.upload.threshold
357,913,941
536,870,912
536,870,912

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s3.network.baseline.bandwidth

The baseline for assessing local network bandwidth should be the network’s stable capability to achieve both outbound and inbound bandwidth. Since the server internally performs operations such as writing the WAL, S3, and Compaction, each data write from a client translates into three network writes by the server. By considering the business’s read/write ratio, you can ultimately determine the maximum write load a single machine can manage.