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Fix it, then Ship it!
A couple of smaller points below, with the largest being the somewhat blurry
handling of time-based executions.
src/main/java/org/apache/aurora/scheduler/BatchWorker.java (line 197)
`readyItems` is still a left over from the previous patch version. Could be
renamed to just `batch`.
src/main/java/org/apache/aurora/scheduler/BatchWorker.java (line 228)
Do you have any particular usecase for this metric?
We already have `batchesProcessed` and `itemsProcessed` and can compute the
rate of processed items and batches. This seems more robust to me than just
looking at `lastBatchSize`.
73 - 87)
This code is exposing a slight design smell in my eye: We are using the
`DelayedExecutor` to trigger the `batchWorker` when a backoff timer has passed.
However, the latter already provides an internal backoff mechanism.
I'd rather see if we have just one defined way how to handle those
* either the BatchWorker does not perform any backoff handling at all. This
seems to be in line with what Zameer has proposed in his last comment,
* or we make the backoff mechanism a first-class feature of the batchWorker
so that I can say I can inject `backoffStrategy` and `lastBackoffMsec` to be
used for the `WorkItem` created in `batchWorker.execute`.
- Stephan Erb
On Sept. 14, 2016, 6:47 p.m., Maxim Khutornenko wrote:
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> (Updated Sept. 14, 2016, 6:47 p.m.)
> Review request for Aurora, Joshua Cohen, Stephan Erb, and Zameer Manji.
> Repository: aurora
> This is the first (out of 3) patches intending to reduce storage write lock
> contention and as such improve overall system write throughput. It introduces
> the `BatchWorker` and migrates the majority of storage writes due to task
> status change events to use `TaskEventBatchWorker`.
> Our current storage system writes effectively behave as `SERIALIZABLE`
> transaction isolation level in SQL terms. This means all writes require
> exclusive access to the storage and no two transactions can happen in
> parallel . While it certainly simplifies our implementation, it creates a
> single hotspot where multiple threads are competing for the storage write
> access. This type of contention only worsens as the cluster size grows, more
> tasks are scheduled, more status updates are processed, more subscribers are
> listening to status updates and etc. Eventually, the scheduler throughput
> (and especially task scheduling) becomes degraded to the extent that certain
> operations wait much longer (4x and more) for the lock acquisition than it
> takes to process their payload when inside the transaction. Some ops (like
> event processing) are generally tolerant of these types of delays. Others -
> not as much. The task scheduling suffers the most as backing up the
> scheduling queue directly affects
the Median Time To Assigned (MTTA).
> Given the above, it's natural to assume that reducing the number of write
> transactions should help reducing the lock contention. This patch introduces
> a generic `BatchWorker` service that delivers a "best effort" batching
> approach by redirecting multiple individual write requests into a single FIFO
> queue served non-stop by a single dedicated thread. Every batch shares a
> single write transaction thus reducing the number of potential write lock
> requests. To minimize wait-in-queue time, items are dispatched immediately
> and the max number of items is bounded. There are a few `BatchWorker`
> instances specialized on particular workload types: task even processing,
> cron scheduling and task scheduling. Every instance can be tuned
> independently (max batch size) and provides specialized metrics helping to
> monitor each workload type perf.
> The proposed approach has been heavily tested in production and delivered the
> best results. The lock contention latencies got down between 2x and 5x
> depending on the cluster load. A number of other approaches tried but
> discarded as not performing well or even performing much worse than the
> current master:
> - Clock-driven batch execution - every batch is dispatched on a time schedule
> - Max batch with a deadline - a batch is dispatched when max size is reached
> OR a timeout expires
> - Various combinations of the above - some `BatchWorkers` are using
> clock-driven execution while others are using max batch with a deadline
> - Completely non-blocking (event-based) completion notification - all call
> sites are notified of item completion via a `BatchWorkCompleted` event
> Happy to provide more details on the above if interested.
> The introduction of the `BatchWorker` by itself was not enough to
> substantially improve the MTTA. It, however, paves the way for the next phase
> of scheduling perf improvement - taking more than 1 task from a given
> `TaskGroup` in a single scheduling round (coming soon). That improvement
> wouldn't deliver without decreasing the lock contention first.
> Note: it wasn't easy to have a clean diff split, so some functionality in
> `BatchWorker` (e.g.: `executeWithReplay`) appears to be unused in the current
> patch but will become obvious in the part 2 (coming out shortly).
>  -
> src/main/java/org/apache/aurora/scheduler/BatchWorker.java PRE-CREATION
> src/test/java/org/apache/aurora/scheduler/BatchWorkerTest.java PRE-CREATION
> Diff: https://reviews.apache.org/r/51759/diff/
> All types of testing including deploying to test and production clusters.
> Maxim Khutornenko