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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339

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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831

This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.

The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.

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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.

@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?

@wjones127
wjones127force-pushed the ARROW-14908-windows-join-crash branch from 3de21c0 to 507050bCompareFebruary 9, 2022 22:21
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
@wjones127wjones127 changed the title ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
wjones127 marked this pull request as ready for review February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
@wjones127
wjones127force-pushed the ARROW-14908-windows-join-crash branch from 9a510cb to a61b7a4CompareFebruary 11, 2022 17:40
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)

Comment threadr/tests/testthat/test-dplyr-join.R Outdated
Comment threadr/tests/testthat/test-dplyr-join.R Outdated
Comment threadr/tests/testthat/test-dplyr-join.R Outdated
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Looks good! Thanks for figuring this out.

Comment threadcpp/src/arrow/compute/exec/hash_join.cc Outdated
Comment threadcpp/src/arrow/compute/exec/hash_join_dict.cc Outdated
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.
Conbench compare runs links:
[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2
[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm
[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x
[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q
Supported benchmarks:
ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True
test-mac-arm: Supported benchmark langs: C++, Python, R
ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript
ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java

kszucs pushed a commit to kszucs/arrow that referenced this pull request Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127 mentioned this pull request Apr 8, 2022
Closed
westonpace pushed a commit that referenced this pull request Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport mentioned this pull request Nov 23, 2022
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
@wjones127
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
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February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
@wjones127
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Looks good! Thanks for figuring this out.
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Comment threadcpp/src/arrow/compute/exec/hash_join_dict.cc
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
to kszucs/arrow
that referenced
this pull request
Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
mentioned this pull request
Apr 8, 2022
 Closed

westonpace pushed a commit
that referenced
this pull request
Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
mentioned this pull request
Nov 23, 2022

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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
@wjones127
wjones127force-pushed
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
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marked this pull request as ready for review
February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
@wjones127
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Looks good! Thanks for figuring this out.
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Comment threadcpp/src/arrow/compute/exec/hash_join_dict.cc
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
to kszucs/arrow
that referenced
this pull request
Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
mentioned this pull request
Apr 8, 2022
 Closed

westonpace pushed a commit
that referenced
this pull request
Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
mentioned this pull request
Nov 23, 2022

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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
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February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Looks good! Thanks for figuring this out.
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
to kszucs/arrow
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Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
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Apr 8, 2022
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Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
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marked this pull request as ready for review
February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Looks good! Thanks for figuring this out.
Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
to kszucs/arrow
that referenced
this pull request
Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
mentioned this pull request
Apr 8, 2022
 Closed

westonpace pushed a commit
that referenced
this pull request
Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
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Nov 23, 2022

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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
@wjones127
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
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February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Looks good! Thanks for figuring this out.
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
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@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
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Apr 8, 2022
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Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
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February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
@wjones127
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Co-authored-by: Jonathan Keane <jkeane@gmail.com>
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Looks good! Thanks for figuring this out.
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Comment threadcpp/src/arrow/compute/exec/hash_join_dict.cc
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
to kszucs/arrow
that referenced
this pull request
Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
mentioned this pull request
Apr 8, 2022
 Closed

westonpace pushed a commit
that referenced
this pull request
Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
mentioned this pull request
Nov 23, 2022

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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows by wjones127 · Pull Request #12339 · apache/arrow · GitHub
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows - #12339
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows#12339
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Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
This only fails on Windows. On any platform, when USE_THREADS = FALSE we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the InputRecieved() callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which USE_THREADS=FALSE sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
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My best guess right now is that some memory is getting clobbered by another thread. Is there a way to execute on a single thread somehow? Tried set_cpu_count(1) and set_io_thread_count(1) (and also USE_THREADS=FALSE is default on Windows), but same issue.
@jonkeane Any thoughts on the threading settings?
@bkietz I know isn't a lot to go off of, but anything stand out to you in the above tracebacks?
@wjones127
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Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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ARROW-14908: [C++][R] Dataset hash join segfaults on Windows [WIP]ARROW-14908: [C++][R] Dataset hash join segfaults on WindowsFeb 11, 2022
@wjones127
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marked this pull request as ready for review
February 11, 2022 17:39
@wjones127
Add one to thread count
a61b7a4
The main thread touches the thread_indexer before it's used by the
worker thread, so we need to make sure it has capacity for both
threads.
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Thanks for all of your work on this, I know it's been a lot. A few comments (mostly on linting)
Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Comment threadr/tests/testthat/test-dplyr-join.R
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Apply suggestions from code review
8da2b1c
Co-authored-by: Jonathan Keane <jkeane@gmail.com>
@wjones127
Use withr to change options
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Looks good! Thanks for figuring this out.
Comment threadcpp/src/arrow/compute/exec/hash_join.cc
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Comment threadcpp/src/arrow/compute/exec/hash_join_dict.cc
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Benchmark runs are scheduled for baseline = 5ad5ddc and contender = 7b5efe4. 7b5efe4 is a master commit associated with this PR. Results will be available as each benchmark for each run completes.

Conbench compare runs links:

[Finished ⬇️0.0% ⬆️0.0%] ec2-t3-xlarge-us-east-2

[Finished ⬇️0.81% ⬆️0.0%] test-mac-arm

[Failed ⬇️0.36% ⬆️0.0%] ursa-i9-9960x

[Finished ⬇️0.13% ⬆️0.09%] ursa-thinkcentre-m75q

Supported benchmarks:

ec2-t3-xlarge-us-east-2: Supported benchmark langs: Python. Runs only benchmarks with cloud = True

test-mac-arm: Supported benchmark langs: C++, Python, R

ursa-i9-9960x: Supported benchmark langs: Python, R, JavaScript

ursa-thinkcentre-m75q: Supported benchmark langs: C++, Java
kszucs pushed a commit
to kszucs/arrow
that referenced
this pull request
Mar 3, 2022
@wjones127@kszucs
ARROW-14908: [C++][R] Dataset hash join segfaults on Windows
411b5ee
Test failure on my branch: https://github.com/wjones127/arrow/runs/5068285944?check_suite_focus=true#step:18:27831
~This only fails on Windows~. On any platform, when `USE_THREADS = FALSE` we cannot execute an exec plan that joins after scanning from a dataset.
The source node executes the `InputRecieved()` callback in the IO thread, while the HashJoin wasn't anticipating another thread if executor is null (which `USE_THREADS=FALSE` sets). This PR adds one to the thread local state vector size to anticipate this case of 1 main thread + 1 IO thread.
Closesapache#12339 from wjones127/ARROW-14908-windows-join-crash
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@wjones127wjones127
mentioned this pull request
Apr 8, 2022
 Closed

westonpace pushed a commit
that referenced
this pull request
Apr 21, 2022
@wjones127@westonpace
ARROW-15718: [C++] Increase thread limit to work around thread issues
08ab8b0
In #12339 we added one, which enabled joining one table to one dataset using `use_threads=false`. However, I found that joining two datasets hit the thread limit.
There are plans to find [a long-term fix](https://issues.apache.org/jira/browse/ARROW-16072) that can run these operations synchronously with fewer threads, but that won't be ready for the next release.
As a temporary fix for 8.0.0, I propose just bumping up the `local_states_` capacity.
Closes#12845 from wjones127/ARROW-15718-multiple-datasets
Authored-by: Will Jones <willjones127@gmail.com>
Signed-off-by: Weston Pace <weston.pace@gmail.com>
@asfimportasfimport
mentioned this pull request
Nov 23, 2022

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