Azure blob storage support in Java feature server #2319
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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
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Hi, Thanks for creating this issue, our application is very latency critical and python server is not able to meet the requirement. Can I know if there is any update for this. We are using feast 0.19.4 |
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Hi! I would recommend moving forward solving this through using the Go feature server (https://github.com/feast-dev/feast/blob/projectMetadata/go/internal/feast/registry/registry.go#L319) We're just finishing stabilization of this and it should also be easier to configure CC @samuel100 . This'll be made easier once we migrate the Azure connector into the main repo |
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This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions. |
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- Add azure blob storage support in java feature server - Fix S3 integration test to work without a real AWS account - Add GCS mock to integration tests to be able to run them without a real google cloud account - Adding dependency management in maven for libraries with older incompatible versions as transitive dependencies
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- Add azure blob storage support in java feature server - Fix S3 integration test to work without a real AWS account - Add GCS mock to integration tests to be able to run them without a real google cloud account - Adding dependency management in maven for libraries with older incompatible versions as transitive dependencies
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- Add azure blob storage support in java feature server - Fix S3 integration test to work without a real AWS account - Add GCS mock to integration tests to be able to run them without a real google cloud account - Adding dependency management in maven for libraries with older incompatible versions as transitive dependencies Signed-off-by: Ferenc Szabó <[email protected]>
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- Add azure blob storage support in java feature server - Fix S3 integration test to work without a real AWS account - Add GCS mock to integration tests to be able to run them without a real google cloud account - Adding dependency management in maven for libraries with older incompatible versions as transitive dependencies Signed-off-by: Ferenc Szabó <[email protected]>
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# [0.36.0](v0.35.0...v0.36.0) (2024-04-16) ### Bug Fixes * Add __eq__, __hash__ to SparkSource for correct comparison ([#4028](#4028)) ([e703b40](e703b40)) * Add conn.commit() to Postgresonline_write_batch.online_write_batch ([#3904](#3904)) ([7d75fc5](7d75fc5)) * Add missing __init__.py to embedded_go ([#4051](#4051)) ([6bb4c73](6bb4c73)) * Add missing init files in infra utils ([#4067](#4067)) ([54910a1](54910a1)) * Added registryPath parameter documentation in WebUI reference ([#3983](#3983)) ([5e0af8f](5e0af8f)), closes [#3974](#3974) [#3974](#3974) * Adding missing init files in materialization modules ([#4052](#4052)) ([df05253](df05253)) * Allow trancated timestamps when converting ([#3861](#3861)) ([bdd7dfb](bdd7dfb)) * Azure blob storage support in Java feature server ([#2319](#2319)) ([#4014](#4014)) ([b9aabbd](b9aabbd)) * Bugfix for grabbing historical data from Snowflake with array type features. ([#3964](#3964)) ([1cc94f2](1cc94f2)) * Bytewax materialization engine fails when loading feature_store.yaml ([#3912](#3912)) ([987f0fd](987f0fd)) * CI unittest warnings ([#4006](#4006)) ([0441b8b](0441b8b)) * Correct the returning class proto type of StreamFeatureView to StreamFeatureViewProto instead of FeatureViewProto. ([#3843](#3843)) ([86d6221](86d6221)) * Create index only if not exists during MySQL online store update ([#3905](#3905)) ([2f99a61](2f99a61)) * Disable minio tests in workflows on master and nightly ([#4072](#4072)) ([c06dda8](c06dda8)) * Disable the Feast Usage feature by default. ([#4090](#4090)) ([b5a7013](b5a7013)) * Dump repo_config by alias ([#4063](#4063)) ([e4bef67](e4bef67)) * Extend SQL registry config with a sqlalchemy_config_kwargs key ([#3997](#3997)) ([21931d5](21931d5)) * Feature Server image startup in OpenShift clusters ([#4096](#4096)) ([9efb243](9efb243)) * Fix copy method for StreamFeatureView ([#3951](#3951)) ([cf06704](cf06704)) * Fix for materializing entityless feature views in Snowflake ([#3961](#3961)) ([1e64c77](1e64c77)) * Fix type mapping spark ([#4071](#4071)) ([3afa78e](3afa78e)) * Fix typo as the cli does not support shortcut-f option. ([#3954](#3954)) ([dd79dbb](dd79dbb)) * Get container host addresses from testcontainers ([#3946](#3946)) ([2cf1a0f](2cf1a0f)) * Handle ComplexFeastType to None comparison ([#3876](#3876)) ([fa8492d](fa8492d)) * Hashlib md5 errors in FIPS for python 3.9+ ([#4019](#4019)) ([6d9156b](6d9156b)) * Making the query_timeout variable as optional int because upstream is considered to be optional ([#4092](#4092)) ([fd5b620](fd5b620)) * Move gRPC dependencies to an extra ([#3900](#3900)) ([f93c5fd](f93c5fd)) * Prevent spamming pull busybox from dockerhub ([#3923](#3923)) ([7153cad](7153cad)) * Quickstart notebook example ([#3976](#3976)) ([b023aa5](b023aa5)) * Raise error when not able read of file source spark source ([#4005](#4005)) ([34cabfb](34cabfb)) * remove not use input parameter in spark source ([#3980](#3980)) ([7c90882](7c90882)) * Remove parentheses in pull_latest_from_table_or_query ([#4026](#4026)) ([dc4671e](dc4671e)) * Remove proto-plus imports ([#4044](#4044)) ([ad8f572](ad8f572)) * Remove unnecessary dependency on mysqlclient ([#3925](#3925)) ([f494f02](f494f02)) * Restore label check for all actions using pull_request_target ([#3978](#3978)) ([591ba4e](591ba4e)) * Revert mypy config ([#3952](#3952)) ([6b8e96c](6b8e96c)) * Rewrite Spark materialization engine to use mapInPandas ([#3936](#3936)) ([dbb59ba](dbb59ba)) * Run feature server w/o gunicorn on windows ([#4024](#4024)) ([584e9b1](584e9b1)) * SqlRegistry _apply_object update statement ([#4042](#4042)) ([ef62def](ef62def)) * Substrait ODFVs for online ([#4064](#4064)) ([26391b0](26391b0)) * Swap security label check on the PR title validation job to explicit permissions instead ([#3987](#3987)) ([f604af9](f604af9)) * Transformation server doesn't generate files from proto ([#3902](#3902)) ([d3a2a45](d3a2a45)) * Trino as an OfflineStore Access Denied when BasicAuthenticaion ([#3898](#3898)) ([49d2988](49d2988)) * Trying to import pyspark lazily to avoid the dependency on the library ([#4091](#4091)) ([a05cdbc](a05cdbc)) * Typo Correction in Feast UI Readme ([#3939](#3939)) ([c16e5af](c16e5af)) * Update actions/setup-python from v3 to v4 ([#4003](#4003)) ([ee4c4f1](ee4c4f1)) * Update typeguard version to >=4.0.0 ([#3837](#3837)) ([dd96150](dd96150)) * Upgrade sqlalchemy from 1.x to 2.x regarding PVE-2022-51668. ([#4065](#4065)) ([ec4c15c](ec4c15c)) * Use CopyFrom() instead of __deepycopy__() for creating a copy of protobuf object. ([#3999](#3999)) ([5561b30](5561b30)) * Using version args to install the correct feast version ([#3953](#3953)) ([b83a702](b83a702)) * Verify the existence of Registry tables in snowflake before calling CREATE sql command. Allow read-only user to call feast apply. ([#3851](#3851)) ([9a3590e](9a3590e)) ### Features * Add duckdb offline store ([#3981](#3981)) ([161547b](161547b)) * Add Entity df in format of a Spark Dataframe instead of just pd.DataFrame or string for SparkOfflineStore ([#3988](#3988)) ([43b2c28](43b2c28)) * Add gRPC Registry Server ([#3924](#3924)) ([373e624](373e624)) * Add local tests for s3 registry using minio ([#4029](#4029)) ([d82d1ec](d82d1ec)) * Add python bytes to array type conversion support proto ([#3874](#3874)) ([8688acd](8688acd)) * Add python client for remote registry server ([#3941](#3941)) ([42a7b81](42a7b81)) * Add Substrait-based ODFV transformation ([#3969](#3969)) ([9e58bd4](9e58bd4)) * Add support for arrays in snowflake ([#3769](#3769)) ([8d6bec8](8d6bec8)) * Added delete_table to redis online store ([#3857](#3857)) ([03dae13](03dae13)) * Adding support for Native Python feature transformations for ODFVs ([#4045](#4045)) ([73bc853](73bc853)) * Bumping requirements ([#4079](#4079)) ([1943056](1943056)) * Decouple transformation types from ODFVs ([#3949](#3949)) ([0a9fae8](0a9fae8)) * Dropping Python 3.8 from local integration tests and integration tests ([#3994](#3994)) ([817995c](817995c)) * Dropping python 3.8 requirements files from the project. ([#4021](#4021)) ([f09c612](f09c612)) * Dropping the support for python 3.8 version from feast ([#4010](#4010)) ([a0f7472](a0f7472)) * Dropping unit tests for Python 3.8 ([#3989](#3989)) ([60f24f9](60f24f9)) * Enable Arrow-based columnar data transfers ([#3996](#3996)) ([d8d7567](d8d7567)) * Enable Vector database and retrieve_online_documents API ([#4061](#4061)) ([ec19036](ec19036)) * Kubernetes materialization engine written based on bytewax ([#4087](#4087)) ([7617bdb](7617bdb)) * Lint with ruff ([#4043](#4043)) ([7f1557b](7f1557b)) * Make arrow primary interchange for offline ODFV execution ([#4083](#4083)) ([9ed0a09](9ed0a09)) * Pandas v2 compatibility ([#3957](#3957)) ([64459ad](64459ad)) * Pull duckdb from contribs, add to CI ([#4059](#4059)) ([318a2b8](318a2b8)) * Refactor ODFV schema inference ([#4076](#4076)) ([c50a9ff](c50a9ff)) * Refactor registry caching logic into a separate class ([#3943](#3943)) ([924f944](924f944)) * Rename OnDemandTransformations to Transformations ([#4038](#4038)) ([9b98eaf](9b98eaf)) * Revert updating dependencies so that feast can be run on 3.11. ([#3968](#3968)) ([d3c68fb](d3c68fb)), closes [#3958](#3958) * Rewrite ibis point-in-time-join w/o feast abstractions ([#4023](#4023)) ([3980e0c](3980e0c)) * Support s3gov schema by snowflake offline store during materialization ([#3891](#3891)) ([ea8ad17](ea8ad17)) * Update odfv test ([#4054](#4054)) ([afd52b8](afd52b8)) * Update pyproject.toml to use Python 3.9 as default ([#4011](#4011)) ([277b891](277b891)) * Update the Pydantic from v1 to v2 ([#3948](#3948)) ([ec11a7c](ec11a7c)) * Updating dependencies so that feast can be run on 3.11. ([#3958](#3958)) ([59639db](59639db)) * Updating protos to separate transformation ([#4018](#4018)) ([c58ef74](c58ef74)) ### Reverts * Reverting bumping requirements ([#4081](#4081)) ([1ba65b4](1ba65b4)), closes [#4079](#4079) * Verify the existence of Registry tables in snowflake… ([#3907](#3907)) ([c0d358a](c0d358a)), closes [#3851](#3851)
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Expected Behavior
Feast Java feature servers should be able to read from a registry in Azure blob storage.
Current Behavior
Azure users can use the python feature server through https://github.com/Azure/feast-azure/tree/main/cluster/sdk or use an old Spark centric approach for feature serving. We should enable Java serving support as well
Possible Solution
https://github.com/feast-dev/feast/blob/master/java/serving/src/main/java/feast/serving/config/RegistryConfig.java#L48 has AWS/GCP equivalents. We should implement the interface for Azure.
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