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2021-05-17parallel-checkout: send the new object_id algo field to the workersMatheus Tavares
An object_id storing a SHA-1 name has some unused bytes at the end of the hash array. Since these bytes are not used, they are usually not initialized to any value either. However, at parallel_checkout.c:send_one_item() the object_id of a cache entry is copied into a buffer which is later sent to a checkout worker through a pipe write(). This makes Valgrind complain about passing uninitialized bytes to a syscall. The worker won't use these uninitialized bytes either, but the warning could confuse someone trying to debug this code; So instead of using oidcpy(), send_one_item() uses hashcpy() to only copy the used/initialized bytes of the object_id, and leave the remaining part with zeros. However, since cf0983213c ("hash: add an algo member to struct object_id", 2021-04-26), using hashcpy() is no longer sufficient here as it won't copy the new algo field from the object_id. Let's add and use a new function which meets both our requirements of copying all the important object_id data while still avoiding the uninitialized bytes, by padding the end of the hash array in the destination object_id. With this change, we also no longer need the destination buffer from send_one_item() to be initialized with zeros, so let's switch from xcalloc() to xmalloc() to make this clear. Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2021-05-05ci: run test round with parallel-checkout enabledMatheus Tavares
We already have tests for the basic parallel-checkout operations. But this code can also run be executed by other commands, such as git-read-tree and git-sparse-checkout, which are currently not tested with multiple workers. To promote a wider test coverage without duplicating tests: 1. Add the GIT_TEST_CHECKOUT_WORKERS environment variable, to optionally force parallel-checkout execution during the whole test suite. 2. Set this variable (with a value of 2) in the second test round of our linux-gcc CI job. This round runs `make test` again with some optional GIT_TEST_* variables enabled, so there is no additional overhead in exercising the parallel-checkout code here. Note that tests checking out less than two parallel-eligible entries will fall back to the sequential mode. Nevertheless, it's still a good exercise for the parallel-checkout framework as the fallback codepath also writes the queued entries using the parallel-checkout functions (only without spawning any worker). Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2021-05-05parallel-checkout: add tests related to path collisionsMatheus Tavares
Add tests to confirm that path collisions are properly detected by checkout workers, both to avoid race conditions and to report colliding entries on clone. Co-authored-by: Jeff Hostetler <jeffhost@microsoft.com> Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2021-04-19parallel-checkout: support progress displayingMatheus Tavares
Original-patch-by: Nguyễn Thái Ngọc Duy <pclouds@gmail.com> Signed-off-by: Nguyễn Thái Ngọc Duy <pclouds@gmail.com> Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2021-04-19parallel-checkout: add configuration optionsMatheus Tavares
Make parallel checkout configurable by introducing two new settings: checkout.workers and checkout.thresholdForParallelism. The first defines the number of workers (where one means sequential checkout), and the second defines the minimum number of entries to attempt parallel checkout. To decide the default value for checkout.workers, the parallel version was benchmarked during three operations in the linux repo, with cold cache: cloning v5.8, checking out v5.8 from v2.6.15 (checkout I) and checking out v5.8 from v5.7 (checkout II). The four tables below show the mean run times and standard deviations for 5 runs in: a local file system on SSD, a local file system on HDD, a Linux NFS server, and Amazon EFS (all on Linux). Each parallel checkout test was executed with the number of workers that brings the best overall results in that environment. Local SSD: Sequential 10 workers Speedup Clone 8.805 s ± 0.043 s 3.564 s ± 0.041 s 2.47 ± 0.03 Checkout I 9.678 s ± 0.057 s 4.486 s ± 0.050 s 2.16 ± 0.03 Checkout II 5.034 s ± 0.072 s 3.021 s ± 0.038 s 1.67 ± 0.03 Local HDD: Sequential 10 workers Speedup Clone 32.288 s ± 0.580 s 30.724 s ± 0.522 s 1.05 ± 0.03 Checkout I 54.172 s ± 7.119 s 54.429 s ± 6.738 s 1.00 ± 0.18 Checkout II 40.465 s ± 2.402 s 38.682 s ± 1.365 s 1.05 ± 0.07 Linux NFS server (v4.1, on EBS, single availability zone): Sequential 32 workers Speedup Clone 240.368 s ± 6.347 s 57.349 s ± 0.870 s 4.19 ± 0.13 Checkout I 242.862 s ± 2.215 s 58.700 s ± 0.904 s 4.14 ± 0.07 Checkout II 65.751 s ± 1.577 s 23.820 s ± 0.407 s 2.76 ± 0.08 EFS (v4.1, replicated over multiple availability zones): Sequential 32 workers Speedup Clone 922.321 s ± 2.274 s 210.453 s ± 3.412 s 4.38 ± 0.07 Checkout I 1011.300 s ± 7.346 s 297.828 s ± 0.964 s 3.40 ± 0.03 Checkout II 294.104 s ± 1.836 s 126.017 s ± 1.190 s 2.33 ± 0.03 The above benchmarks show that parallel checkout is most effective on repositories located on an SSD or over a distributed file system. For local file systems on spinning disks, and/or older machines, the parallelism does not always bring a good performance. For this reason, the default value for checkout.workers is one, a.k.a. sequential checkout. To decide the default value for checkout.thresholdForParallelism, another benchmark was executed in the "Local SSD" setup, where parallel checkout showed to be beneficial. This time, we compared the runtime of a `git checkout -f`, with and without parallelism, after randomly removing an increasing number of files from the Linux working tree. The "sequential fallback" column below corresponds to the executions where checkout.workers was 10 but checkout.thresholdForParallelism was equal to the number of to-be-updated files plus one (so that we end up writing sequentially). Each test case was sampled 15 times, and each sample had a randomly different set of files removed. Here are the results: sequential fallback 10 workers speedup 10 files 772.3 ms ± 12.6 ms 769.0 ms ± 13.6 ms 1.00 ± 0.02 20 files 780.5 ms ± 15.8 ms 775.2 ms ± 9.2 ms 1.01 ± 0.02 50 files 806.2 ms ± 13.8 ms 767.4 ms ± 8.5 ms 1.05 ± 0.02 100 files 833.7 ms ± 21.4 ms 750.5 ms ± 16.8 ms 1.11 ± 0.04 200 files 897.6 ms ± 30.9 ms 730.5 ms ± 14.7 ms 1.23 ± 0.05 500 files 1035.4 ms ± 48.0 ms 677.1 ms ± 22.3 ms 1.53 ± 0.09 1000 files 1244.6 ms ± 35.6 ms 654.0 ms ± 38.3 ms 1.90 ± 0.12 2000 files 1488.8 ms ± 53.4 ms 658.8 ms ± 23.8 ms 2.26 ± 0.12 From the above numbers, 100 files seems to be a reasonable default value for the threshold setting. Note: Up to 1000 files, we observe a drop in the execution time of the parallel code with an increase in the number of files. This is a rather odd behavior, but it was observed in multiple repetitions. Above 1000 files, the execution time increases according to the number of files, as one would expect. About the test environments: Local SSD tests were executed on an i7-7700HQ (4 cores with hyper-threading) running Manjaro Linux. Local HDD tests were executed on an Intel(R) Xeon(R) E3-1230 (also 4 cores with hyper-threading), HDD Seagate Barracuda 7200.14 SATA 3.1, running Debian. NFS and EFS tests were executed on an Amazon EC2 c5n.xlarge instance, with 4 vCPUs. The Linux NFS server was running on a m6g.large instance with 2 vCPUSs and a 1 TB EBS GP2 volume. Before each timing, the linux repository was removed (or checked out back to its previous state), and `sync && sysctl vm.drop_caches=3` was executed. Co-authored-by: Jeff Hostetler <jeffhost@microsoft.com> Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2021-04-19parallel-checkout: make it truly parallelMatheus Tavares
Use multiple worker processes to distribute the queued entries and call write_pc_item() in parallel for them. The items are distributed uniformly in contiguous chunks. This minimizes the chances of two workers writing to the same directory simultaneously, which could affect performance due to lock contention in the kernel. Work stealing (or any other format of re-distribution) is not implemented yet. The protocol between the main process and the workers is quite simple. They exchange binary messages packed in pkt-line format, and use PKT-FLUSH to mark the end of input (from both sides). The main process starts the communication by sending N pkt-lines, each corresponding to an item that needs to be written. These packets contain all the necessary information to load, smudge, and write the blob associated with each item. Then it waits for the worker to send back N pkt-lines containing the results for each item. The resulting packet must contain: the identification number of the item that it refers to, the status of the operation, and the lstat() data gathered after writing the file (iff the operation was successful). For now, checkout always uses a hardcoded value of 2 workers, only to demonstrate that the parallel checkout framework correctly divides and writes the queued entries. The next patch will add user configurations and define a more reasonable default, based on tests with the said settings. Co-authored-by: Nguyễn Thái Ngọc Duy <pclouds@gmail.com> Co-authored-by: Jeff Hostetler <jeffhost@microsoft.com> Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>
2021-04-19unpack-trees: add basic support for parallel checkoutMatheus Tavares
This new interface allows us to enqueue some of the entries being checked out to later uncompress them, apply in-process filters, and write out the files in parallel. For now, the parallel checkout machinery is enabled by default and there is no user configuration, but run_parallel_checkout() just writes the queued entries in sequence (without spawning additional workers). The next patch will actually implement the parallelism and, later, we will make it configurable. Note that, to avoid potential data races, not all entries are eligible for parallel checkout. Also, paths that collide on disk (e.g. case-sensitive paths in case-insensitive file systems), are detected by the parallel checkout code and skipped, so that they can be safely sequentially handled later. The collision detection works like the following: - If the collision was at basename (e.g. 'a/b' and 'a/B'), the framework detects it by looking for EEXIST and EISDIR errors after an open(O_CREAT | O_EXCL) failure. - If the collision was at dirname (e.g. 'a/b' and 'A'), it is detected at the has_dirs_only_path() check, which is done for the leading path of each item in the parallel checkout queue. Both verifications rely on the fact that, before enqueueing an entry for parallel checkout, checkout_entry() makes sure that there is no file at the entry's path and that its leading components are all real directories. So, any later change in these conditions indicates that there was a collision (either between two parallel-eligible entries or between an eligible and an ineligible one). After all parallel-eligible entries have been processed, the collided (and thus, skipped) entries are sequentially fed to checkout_entry() again. This is similar to the way the current code deals with collisions, overwriting the previously checked out entries with the subsequent ones. The only difference is that, since we no longer create the files in the same order that they appear on index, we are not able to determine which of the colliding entries will survive on disk (for the classic code, it is always the last entry). Co-authored-by: Nguyễn Thái Ngọc Duy <pclouds@gmail.com> Co-authored-by: Jeff Hostetler <jeffhost@microsoft.com> Signed-off-by: Matheus Tavares <matheus.bernardino@usp.br> Signed-off-by: Junio C Hamano <gitster@pobox.com>