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fetching: export utilities for decompressing and parsing partition fetch responses #4

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dimitarvdimitrov
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This pulls in twmb#803. There were conflicts with #1 in the signature of ProcessRespPartition. After chatting with @ortuman we agreed to keep the field private for now

…tch responses

### Background

In grafana/mimir we are working towards making fetch requests ourselves. The primary reason behind that is that individual requests to the kafka backend are slow, so doing them sequentially per partition becomes the bottleneck in our application. So we want to fetch records in parallel to speed up the consumption.

One difficulty I met when issuing `FetchRequest`s ourselves is that parsing the response is non-trivial. That's why I'm proposing to export these functions for downstream projects to use.

Alternatively, I can also try contributing the concurrent fetching logic. But I believe that is much more nuanced and with more tradeoffs around fetched bytes and latency. So I wasn't sure whether it's a good fit for a general purpose library. I'm open to discuss this further.

### What this PR does

Moves `(*kgo.cursorOffsetNext).processRespPartition` from being a method to being a standalone function - `kgo.processRespPartition`. There were also little changes necessary to make the interface suitable for public use (like removing the `*broker` parameter).

### Side effects

To minimize the necessary changes and the API surface of the package I opted to use a single global decompressor for all messages. Previously, there would be one decompressor per client and that decompressor would be passed down to `(*cursorOffsetNext).processRespPartition`. My understanding is that using different pooled readers (lz4, zst, gzip) shouldn't have a negative impact on performance because usage patterns do not affect the behaviour of the reader (for example, a consistent size of decompressed data doesn't make the reader more or less efficient). I have not thoroughly verified or tested this - Let me know if you think that's important.

An alternative to this is to also export the `decompressor` along with `newDecompressor()` and the auxiliary types for decompression.
@dimitarvdimitrov dimitarvdimitrov changed the title Dimitar/grafana master with export partition parsing utils fetching: export utilities for decompressing and parsing partition fetch responses Sep 30, 2024
@dimitarvdimitrov dimitarvdimitrov merged commit ec37e4b into grafana:master Sep 30, 2024
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ortuman pushed a commit that referenced this pull request Oct 3, 2024
…th-export-partition-parsing-utils

fetching: export utilities for decompressing and parsing partition fetch responses
ortuman added a commit that referenced this pull request Oct 3, 2024
* fetching: export utilities for decompressing and parsing partition retch responses

### Background

In grafana/mimir we are working towards making fetch requests ourselves. The primary reason behind that is that individual requests to the kafka backend are slow, so doing them sequentially per partition becomes the bottleneck in our application. So we want to fetch records in parallel to speed up the consumption.

One difficulty I met when issuing `FetchRequest`s ourselves is that parsing the response is non-trivial. That's why I'm proposing to export these functions for downstream projects to use.

Alternatively, I can also try contributing the concurrent fetching logic. But I believe that is much more nuanced and with more tradeoffs around fetched bytes and latency. So I wasn't sure whether it's a good fit for a general purpose library. I'm open to discuss this further.

### What this PR does

Moves `(*kgo.cursorOffsetNext).processRespPartition` from being a method to being a standalone function - `kgo.processRespPartition`. There were also little changes necessary to make the interface suitable for public use (like removing the `*broker` parameter).

### Side effects

To minimize the necessary changes and the API surface of the package I opted to use a single global decompressor for all messages. Previously, there would be one decompressor per client and that decompressor would be passed down to `(*cursorOffsetNext).processRespPartition`. My understanding is that using different pooled readers (lz4, zst, gzip) shouldn't have a negative impact on performance because usage patterns do not affect the behaviour of the reader (for example, a consistent size of decompressed data doesn't make the reader more or less efficient). I have not thoroughly verified or tested this - Let me know if you think that's important.

An alternative to this is to also export the `decompressor` along with `newDecompressor()` and the auxiliary types for decompression.

* Restore multiline processV0OuterMessage

* `*kgo.Records` pooling support

Signed-off-by: Miguel Ángel Ortuño <ortuman@gmail.com>

* Merge pull request #1 from grafana/ortuman/reduce-kgo-record-alloc

`*kgo.Record` pooling support

* fetching: export utilities for decompressing and parsing partition retch responses

* Merge pull request #4 from dimitarvdimitrov/dimitar/grafana-master-with-export-partition-parsing-utils

fetching: export utilities for decompressing and parsing partition fetch responses

* Merge pull request #3 from ortuman/reduce-decompression-buffer-allocations

Signed-off-by: Miguel Ángel Ortuño <ortuman@gmail.com>

---------

Signed-off-by: Miguel Ángel Ortuño <ortuman@gmail.com>
Co-authored-by: Dimitar Dimitrov <dimitar.dimitrov@grafana.com>
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2 participants