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feat: Add support for arrays in snowflake #3769
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Signed-off-by: john.lemmon <john.lemmon@medely.com>
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I'd still need to update the documentation but I'd like to make sure that at least this approach is fine. And again I'm choosing to not support inferred schemas or the push online store because they both require being able to infer the schema from the Snowflake schema.
Array(Float32), | ||
Array(Bool), | ||
]: | ||
df[feature.name] = [json.loads(x) for x in df[feature.name]] |
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These arrays come in as a json string so this converts them to a list.
"database": os.getenv("SNOWFLAKE_CI_DATABASE", "FEAST"), | ||
"schema": os.getenv("SNOWFLAKE_CI_SCHEMA_ONLINE", "ONLINE"), |
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My company locked down creating a database so it's easier for me to use my provided database/schema as a sandbox. This keeps the default the same but lets me choose the name during testing.
@pytest.mark.parametrize("online_store", [SNOWFLAKE_ONLINE_CONFIG, "sqlite"]) | ||
@pytest.mark.integration | ||
def test_snowflake_materialization_consistency_internal(): | ||
def test_snowflake_materialization_consistency(online_store): | ||
snowflake_config = IntegrationTestRepoConfig( | ||
online_store=SNOWFLAKE_ONLINE_CONFIG, | ||
online_store=online_store, |
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This test was duplicated for each online_store (internal vs external). So I combined them with a parameterize annotation to make that clearer.
@pytest.mark.parametrize( | ||
"feature_dtype, feast_dtype", | ||
[ | ||
("string", Array(String)), | ||
("bytes", Array(Bytes)), | ||
("int32", Array(Int32)), | ||
("int64", Array(Int64)), | ||
("float", Array(Float64)), | ||
("bool", Array(Bool)), | ||
("datetime", Array(UnixTimestamp)), | ||
], | ||
) | ||
@pytest.mark.parametrize("feature_is_empty_list", [False]) | ||
@pytest.mark.parametrize("online_store", [SNOWFLAKE_ONLINE_CONFIG, "sqlite"]) | ||
@pytest.mark.integration | ||
def test_snowflake_materialization_consistency_external(): | ||
def test_snowflake_materialization_consistency_internal_with_lists( |
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This test is similar to the one above but I had to verify the output myself instead of the shared function because I'm using Array types.
It's a lot of individual tests but if needed I can probably run a single test with multiple features to test each data type. It's just a lot more custom code for the setup.
driver_stats_fv = FeatureView( | ||
name="driver_hourly_stats", | ||
entities=[driver], | ||
ttl=timedelta(weeks=52), | ||
schema=schema, |
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These arrays only work with specified schemas (we can't infer what the type is from a plain Array
in Snowflake).
@sfc-gh-madkins Please let me if you're still the right person to review and if you can enable the full tests in Github actions. |
@JohnLemmonMedely Hey John -- thanks for the work on this. I approved this to run, however I am not the right person to review anymore as I have switched focused to the Snowflake Native feature store we announced. |
Thanks @sfc-gh-madkins. Can you add @feast-dev/maintainers as a reviewer? I know things are in flux with Tecton pulling out so I'm not sure who to loop in specifically. Also I don't think the integration tests are running and I don't see the labels on this PR. Is there something else to be done? |
good question on reviewer side. I approved so they should now be running |
lgtm |
Adds support for arrays in snowflake Signed-off-by: john.lemmon <john.lemmon@medely.com> Signed-off-by: tokoko <togurg14@freeuni.edu.ge>
Adds support for arrays in snowflake Signed-off-by: john.lemmon <john.lemmon@medely.com> Signed-off-by: Attila Toth <hello@attilatoth.dev>
Adds support for arrays in snowflake Signed-off-by: john.lemmon <john.lemmon@medely.com>
# [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)
What this PR does / why we need it:
Snowflake doesn't support type-checked arrays but this adds support for arrays where developers have to guarantee the type consistency themselves through the external data pipelines.
This implementation adds support for these data types when stored as an array column in Snowflake:
This does not work with Feast's Feature Inference or the push/spark online store. The schema for these columns has to be defined in Feast because Snowflake itself isn't storing the data type of these variant columns for us to know how to translate them.
Which issue(s) this PR fixes:
Fixes #2280