Make copy fetcher more async #5362
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## main #5362 +/- ##
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- Coverage 90.67% 90.64% -0.03%
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Lines 52524 52533 +9
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- Misses 4898 4914 +16
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Make the copy fetcher more asynchronous by separating the sending of the request for data from the receiving of the response. By doing that, the async append node can send the request to each data node before it starts reading the first response. This can massively improve the performance because the response isn't returned until the remote node has finished executing the query and is ready to return the first tuple.
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This release contains bug fixes since the 2.10.0 release. We recommend that you upgrade at the next available opportunity. **Bugfixes** * timescale#5364 Fix num_chunks inconsistency in hypertables view * timescale#5362 Make copy fetcher more async * timescale#5336 Use NameData and namestrcpy for names * timescale#5317 Fix some incorrect memory handling * timescale#5367 Rename columns in old-style continuous aggregates * timescale#5336 Use NameData and namestrcpy for names * timescale#5343 Set PortalContext when starting job * timescale#5360 Fix uninitialized bucket_info variable * timescale#5362 Make copy fetcher more async * timescale#5364 Fix num_chunks inconsistency in hypertables view * timescale#5367 Fix column name handling in old-style continuous aggregates * timescale#5378 Fix multinode DML HA performance regression * timescale#5384 Fix Hierarchical Continuous Aggregates chunk_interval_size * timescale#5153 Fix concurrent locking with chunk_data_node table **Thanks** * @justinozavala for reporting an issue with PL/Python procedures in the background worker * @Medvecrab for discovering an issue with copying NameData when forming heap tuples. * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns
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This release contains bug fixes since the 2.10.0 release. We recommend that you upgrade at the next available opportunity. **Bugfixes** * timescale#5364 Fix num_chunks inconsistency in hypertables view * timescale#5362 Make copy fetcher more async * timescale#5336 Use NameData and namestrcpy for names * timescale#5317 Fix some incorrect memory handling * timescale#5367 Rename columns in old-style continuous aggregates * timescale#5336 Use NameData and namestrcpy for names * timescale#5343 Set PortalContext when starting job * timescale#5360 Fix uninitialized bucket_info variable * timescale#5362 Make copy fetcher more async * timescale#5364 Fix num_chunks inconsistency in hypertables view * timescale#5367 Fix column name handling in old-style continuous aggregates * timescale#5378 Fix multinode DML HA performance regression * timescale#5384 Fix Hierarchical Continuous Aggregates chunk_interval_size * timescale#5153 Fix concurrent locking with chunk_data_node table **Thanks** * @justinozavala for reporting an issue with PL/Python procedures in the background worker * @Medvecrab for discovering an issue with copying NameData when forming heap tuples. * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns
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This release contains bug fixes since the 2.10.0 release. We recommend that you upgrade at the next available opportunity. **Bugfixes** * timescale#5159 Support Continuous Aggregates names in hypertable_(detailed_)size * timescale#5226 Fix concurrent locking with chunk_data_node table * timescale#5317 Fix some incorrect memory handling * timescale#5336 Use NameData and namestrcpy for names * timescale#5343 Set PortalContext when starting job * timescale#5360 Fix uninitialized bucket_info variable * timescale#5362 Make copy fetcher more async * timescale#5364 Fix num_chunks inconsistency in hypertables view * timescale#5367 Fix column name handling in old-style continuous aggregates * timescale#5378 Fix multinode DML HA performance regression * timescale#5384 Fix Hierarchical Continuous Aggregates chunk_interval_size **Thanks** * @justinozavala for reporting an issue with PL/Python procedures in the background worker * @Medvecrab for discovering an issue with copying NameData when forming heap tuples. * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns
svenklemm
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This release contains bug fixes since the 2.10.0 release. We recommend that you upgrade at the next available opportunity. **Bugfixes** * #5159 Support Continuous Aggregates names in hypertable_(detailed_)size * #5226 Fix concurrent locking with chunk_data_node table * #5317 Fix some incorrect memory handling * #5336 Use NameData and namestrcpy for names * #5343 Set PortalContext when starting job * #5360 Fix uninitialized bucket_info variable * #5362 Make copy fetcher more async * #5364 Fix num_chunks inconsistency in hypertables view * #5367 Fix column name handling in old-style continuous aggregates * #5378 Fix multinode DML HA performance regression * #5384 Fix Hierarchical Continuous Aggregates chunk_interval_size **Thanks** * @justinozavala for reporting an issue with PL/Python procedures in the background worker * @Medvecrab for discovering an issue with copying NameData when forming heap tuples. * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns
svenklemm
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Mar 7, 2023
This release contains bug fixes since the 2.10.0 release. We recommend that you upgrade at the next available opportunity. **Bugfixes** * timescale#5159 Support Continuous Aggregates names in hypertable_(detailed_)size * timescale#5226 Fix concurrent locking with chunk_data_node table * timescale#5317 Fix some incorrect memory handling * timescale#5336 Use NameData and namestrcpy for names * timescale#5343 Set PortalContext when starting job * timescale#5360 Fix uninitialized bucket_info variable * timescale#5362 Make copy fetcher more async * timescale#5364 Fix num_chunks inconsistency in hypertables view * timescale#5367 Fix column name handling in old-style continuous aggregates * timescale#5378 Fix multinode DML HA performance regression * timescale#5384 Fix Hierarchical Continuous Aggregates chunk_interval_size **Thanks** * @justinozavala for reporting an issue with PL/Python procedures in the background worker * @Medvecrab for discovering an issue with copying NameData when forming heap tuples. * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns
svenklemm
added a commit
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Mar 7, 2023
This release contains bug fixes since the 2.10.0 release. We recommend that you upgrade at the next available opportunity. **Bugfixes** * #5159 Support Continuous Aggregates names in hypertable_(detailed_)size * #5226 Fix concurrent locking with chunk_data_node table * #5317 Fix some incorrect memory handling * #5336 Use NameData and namestrcpy for names * #5343 Set PortalContext when starting job * #5360 Fix uninitialized bucket_info variable * #5362 Make copy fetcher more async * #5364 Fix num_chunks inconsistency in hypertables view * #5367 Fix column name handling in old-style continuous aggregates * #5378 Fix multinode DML HA performance regression * #5384 Fix Hierarchical Continuous Aggregates chunk_interval_size **Thanks** * @justinozavala for reporting an issue with PL/Python procedures in the background worker * @Medvecrab for discovering an issue with copying NameData when forming heap tuples. * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns * @pushpeepkmonroe for discovering an issue in upgrading old-style continuous aggregates with renamed columns
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Make the copy fetcher more asynchronous by separating the sending of the request for data from the receiving of the response. By doing that, the async append node can send the request to each data node before it starts reading the first response. This can massively improve the performance because the response isn't returned until the remote node has finished executing the query and is ready to return the first tuple.