fix: Update bytewax materialization#3368
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feast-ci-bot merged 3 commits intofeast-dev:masterfrom Dec 2, 2022
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- Since no data is exchanged between workers, remove k8s service definition. - Update bytewax dataflow to only use one worker. Signed-off-by: Dan Herrera <[email protected]>
Signed-off-by: Dan Herrera <[email protected]>
Signed-off-by: Dan Herrera <[email protected]>
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[APPROVALNOTIFIER] This PR is APPROVED This pull-request has been approved by: adchia, whoahbot The full list of commands accepted by this bot can be found here. The pull request process is described here DetailsNeeds approval from an approver in each of these files:
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# [0.27.0](v0.26.0...v0.27.0) (2022-12-05) ### Bug Fixes * Changing Snowflake template code to avoid query not implemented … ([#3319](#3319)) ([1590d6b](1590d6b)) * Dask zero division error if parquet dataset has only one partition ([#3236](#3236)) ([69e4a7d](69e4a7d)) * Enable Spark materialization on Yarn ([#3370](#3370)) ([0c20a4e](0c20a4e)) * Ensure that Snowflake accounts for number columns that overspecify precision ([#3306](#3306)) ([0ad0ace](0ad0ace)) * Fix memory leak from usage.py not properly cleaning up call stack ([#3371](#3371)) ([a0c6fde](a0c6fde)) * Fix workflow to contain env vars ([#3379](#3379)) ([548bed9](548bed9)) * Update bytewax materialization ([#3368](#3368)) ([4ebe00f](4ebe00f)) * Update the version counts ([#3378](#3378)) ([8112db5](8112db5)) * Updated AWS Athena template ([#3322](#3322)) ([5956981](5956981)) * Wrong UI data source type display ([#3276](#3276)) ([8f28062](8f28062)) ### Features * Cassandra online store, concurrency in bulk write operations ([#3367](#3367)) ([eaf354c](eaf354c)) * Cassandra online store, concurrent fetching for multiple entities ([#3356](#3356)) ([00fa21f](00fa21f)) * Get Snowflake Query Output As Pyspark Dataframe ([#2504](#2504)) ([#3358](#3358)) ([2f18957](2f18957))
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What this PR does / why we need it:
This PR addresses an issue with Bytewax materialization, updates to a more recent version of Bytewax, and removes the creation of services in k8s when running a batch materialization job.