|
| 1 | +""" |
| 2 | +Unit tests for SparkRetrievalJob.persist() and SavedDatasetSparkStorage.from_data_source(). |
| 3 | +
|
| 4 | +Covers the fix for https://github.com/feast-dev/feast/issues/6261 where: |
| 5 | +1. SavedDatasetStorage.from_data_source() did not support SparkSource |
| 6 | +2. SavedDatasetSparkStorage lacked a from_data_source() method |
| 7 | +3. SparkRetrievalJob.persist() only supported table-based storage, not path-based |
| 8 | +""" |
| 9 | + |
| 10 | +from unittest.mock import MagicMock |
| 11 | + |
| 12 | +import pytest |
| 13 | + |
| 14 | +from feast.infra.offline_stores.contrib.spark_offline_store.spark import ( |
| 15 | + SparkOfflineStoreConfig, |
| 16 | + SparkRetrievalJob, |
| 17 | +) |
| 18 | +from feast.infra.offline_stores.contrib.spark_offline_store.spark_source import ( |
| 19 | + SavedDatasetSparkStorage, |
| 20 | + SparkSource, |
| 21 | +) |
| 22 | +from feast.infra.offline_stores.file_source import FileSource |
| 23 | +from feast.infra.online_stores.sqlite import SqliteOnlineStoreConfig |
| 24 | +from feast.repo_config import RepoConfig |
| 25 | +from feast.saved_dataset import SavedDatasetStorage |
| 26 | +from feast.table_format import IcebergFormat |
| 27 | + |
| 28 | +# --------------------------------------------------------------------------- |
| 29 | +# Shared fixtures |
| 30 | +# --------------------------------------------------------------------------- |
| 31 | + |
| 32 | + |
| 33 | +@pytest.fixture() |
| 34 | +def repo_config(): |
| 35 | + return RepoConfig( |
| 36 | + registry="file:///tmp/registry.db", |
| 37 | + project="test", |
| 38 | + provider="local", |
| 39 | + online_store=SqliteOnlineStoreConfig(type="sqlite"), |
| 40 | + offline_store=SparkOfflineStoreConfig(type="spark"), |
| 41 | + ) |
| 42 | + |
| 43 | + |
| 44 | +@pytest.fixture() |
| 45 | +def table_spark_source(): |
| 46 | + return SparkSource( |
| 47 | + name="my_table", |
| 48 | + table="db.my_table", |
| 49 | + timestamp_field="event_timestamp", |
| 50 | + ) |
| 51 | + |
| 52 | + |
| 53 | +@pytest.fixture() |
| 54 | +def path_spark_source(): |
| 55 | + return SparkSource( |
| 56 | + name="my_path_source", |
| 57 | + path="s3a://bucket/data/features/", |
| 58 | + file_format="parquet", |
| 59 | + timestamp_field="event_timestamp", |
| 60 | + ) |
| 61 | + |
| 62 | + |
| 63 | +def _make_spark_retrieval_job(repo_config, remote_warehouse=True): |
| 64 | + """Build a SparkRetrievalJob with a mocked SparkSession.""" |
| 65 | + mock_spark = MagicMock() |
| 66 | + |
| 67 | + if remote_warehouse: |
| 68 | + mock_spark.conf.get.side_effect = lambda key: { |
| 69 | + "hive.metastore.uris": "thrift://metastore:9083", |
| 70 | + }.get(key, None) |
| 71 | + else: |
| 72 | + |
| 73 | + def _local_conf_get(key): |
| 74 | + if key == "hive.metastore.uris": |
| 75 | + raise Exception("not set") |
| 76 | + if key == "spark.sql.warehouse.dir": |
| 77 | + return "file:///tmp/spark-warehouse" |
| 78 | + return None |
| 79 | + |
| 80 | + mock_spark.conf.get.side_effect = _local_conf_get |
| 81 | + |
| 82 | + return SparkRetrievalJob( |
| 83 | + spark_session=mock_spark, |
| 84 | + query="SELECT 1", |
| 85 | + full_feature_names=False, |
| 86 | + config=repo_config, |
| 87 | + ) |
| 88 | + |
| 89 | + |
| 90 | +# --------------------------------------------------------------------------- |
| 91 | +# Group 1: SavedDatasetSparkStorage.from_data_source() |
| 92 | +# --------------------------------------------------------------------------- |
| 93 | + |
| 94 | + |
| 95 | +class TestSavedDatasetSparkStorageFromDataSource: |
| 96 | + def test_from_data_source_with_table_source(self, table_spark_source): |
| 97 | + storage = SavedDatasetSparkStorage.from_data_source(table_spark_source) |
| 98 | + |
| 99 | + assert isinstance(storage, SavedDatasetSparkStorage) |
| 100 | + assert storage.spark_options.table == "db.my_table" |
| 101 | + assert storage.spark_options.query is None |
| 102 | + assert storage.spark_options.path is None |
| 103 | + |
| 104 | + def test_from_data_source_with_path_source(self, path_spark_source): |
| 105 | + storage = SavedDatasetSparkStorage.from_data_source(path_spark_source) |
| 106 | + |
| 107 | + assert isinstance(storage, SavedDatasetSparkStorage) |
| 108 | + assert storage.spark_options.path == "s3a://bucket/data/features/" |
| 109 | + assert storage.spark_options.file_format == "parquet" |
| 110 | + assert storage.spark_options.table is None |
| 111 | + assert storage.spark_options.query is None |
| 112 | + |
| 113 | + def test_from_data_source_rejects_non_spark_source(self): |
| 114 | + file_source = FileSource( |
| 115 | + path="/tmp/data.parquet", |
| 116 | + timestamp_field="event_timestamp", |
| 117 | + ) |
| 118 | + with pytest.raises(AssertionError): |
| 119 | + SavedDatasetSparkStorage.from_data_source(file_source) |
| 120 | + |
| 121 | + |
| 122 | +# --------------------------------------------------------------------------- |
| 123 | +# Group 2: SavedDatasetStorage.from_data_source() dispatch |
| 124 | +# --------------------------------------------------------------------------- |
| 125 | + |
| 126 | + |
| 127 | +class TestSavedDatasetStorageDispatch: |
| 128 | + def test_from_data_source_resolves_spark(self, table_spark_source): |
| 129 | + storage = SavedDatasetStorage.from_data_source(table_spark_source) |
| 130 | + |
| 131 | + assert isinstance(storage, SavedDatasetSparkStorage) |
| 132 | + assert storage.spark_options.table == "db.my_table" |
| 133 | + |
| 134 | + def test_from_data_source_resolves_path_spark(self, path_spark_source): |
| 135 | + storage = SavedDatasetStorage.from_data_source(path_spark_source) |
| 136 | + |
| 137 | + assert isinstance(storage, SavedDatasetSparkStorage) |
| 138 | + assert storage.spark_options.path == "s3a://bucket/data/features/" |
| 139 | + assert storage.spark_options.file_format == "parquet" |
| 140 | + |
| 141 | + def test_roundtrip_table_source(self, table_spark_source): |
| 142 | + storage = SavedDatasetStorage.from_data_source(table_spark_source) |
| 143 | + roundtripped = storage.to_data_source() |
| 144 | + |
| 145 | + assert isinstance(roundtripped, SparkSource) |
| 146 | + assert roundtripped.table == table_spark_source.table |
| 147 | + assert roundtripped.query == table_spark_source.query |
| 148 | + assert roundtripped.path == table_spark_source.path |
| 149 | + |
| 150 | + def test_roundtrip_path_source(self): |
| 151 | + source = SparkSource( |
| 152 | + name="my_path_source", |
| 153 | + table="fallback_name", |
| 154 | + timestamp_field="event_timestamp", |
| 155 | + ) |
| 156 | + storage = SavedDatasetStorage.from_data_source(source) |
| 157 | + roundtripped = storage.to_data_source() |
| 158 | + |
| 159 | + assert isinstance(roundtripped, SparkSource) |
| 160 | + assert roundtripped.table == source.table |
| 161 | + |
| 162 | + |
| 163 | +# --------------------------------------------------------------------------- |
| 164 | +# Group 3: SparkRetrievalJob.persist() |
| 165 | +# --------------------------------------------------------------------------- |
| 166 | + |
| 167 | + |
| 168 | +class TestSparkRetrievalJobPersist: |
| 169 | + def test_persist_with_table_saves_as_table(self, repo_config): |
| 170 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 171 | + storage = SavedDatasetSparkStorage(table="output_table") |
| 172 | + |
| 173 | + job.persist(storage) |
| 174 | + |
| 175 | + mock_df = job.spark_session.sql.return_value |
| 176 | + mock_df.write.saveAsTable.assert_called_once_with("output_table") |
| 177 | + |
| 178 | + def test_persist_with_table_and_format(self, repo_config): |
| 179 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 180 | + storage = SavedDatasetSparkStorage(table="output_table", file_format="parquet") |
| 181 | + |
| 182 | + job.persist(storage) |
| 183 | + |
| 184 | + mock_df = job.spark_session.sql.return_value |
| 185 | + mock_df.write.format.assert_called_once_with("parquet") |
| 186 | + mock_df.write.format.return_value.saveAsTable.assert_called_once_with( |
| 187 | + "output_table" |
| 188 | + ) |
| 189 | + |
| 190 | + def test_persist_with_path_writes_to_path(self, repo_config): |
| 191 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 192 | + storage = SavedDatasetSparkStorage( |
| 193 | + path="s3a://bucket/output/", file_format="parquet" |
| 194 | + ) |
| 195 | + |
| 196 | + job.persist(storage) |
| 197 | + |
| 198 | + mock_df = job.spark_session.sql.return_value |
| 199 | + mock_df.write.format.assert_called_once_with("parquet") |
| 200 | + mock_df.write.format.return_value.mode.assert_called_once_with("error") |
| 201 | + mock_df.write.format.return_value.mode.return_value.save.assert_called_once_with( |
| 202 | + "s3a://bucket/output/" |
| 203 | + ) |
| 204 | + |
| 205 | + def test_persist_with_path_defaults_to_parquet(self, repo_config): |
| 206 | + """When path is set with table_format but no file_format, persist defaults to parquet.""" |
| 207 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 208 | + storage = SavedDatasetSparkStorage( |
| 209 | + path="s3a://bucket/output/", |
| 210 | + file_format=None, |
| 211 | + table_format=IcebergFormat(catalog="test_catalog"), |
| 212 | + ) |
| 213 | + |
| 214 | + job.persist(storage) |
| 215 | + |
| 216 | + mock_df = job.spark_session.sql.return_value |
| 217 | + mock_df.write.format.assert_called_once_with("parquet") |
| 218 | + |
| 219 | + def test_persist_with_path_allow_overwrite(self, repo_config): |
| 220 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 221 | + storage = SavedDatasetSparkStorage( |
| 222 | + path="s3a://bucket/output/", file_format="parquet" |
| 223 | + ) |
| 224 | + |
| 225 | + job.persist(storage, allow_overwrite=True) |
| 226 | + |
| 227 | + mock_df = job.spark_session.sql.return_value |
| 228 | + mock_df.write.format.return_value.mode.assert_called_once_with("overwrite") |
| 229 | + |
| 230 | + def test_persist_with_path_custom_format(self, repo_config): |
| 231 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 232 | + storage = SavedDatasetSparkStorage( |
| 233 | + path="s3a://bucket/output/", file_format="avro" |
| 234 | + ) |
| 235 | + |
| 236 | + job.persist(storage) |
| 237 | + |
| 238 | + mock_df = job.spark_session.sql.return_value |
| 239 | + mock_df.write.format.assert_called_once_with("avro") |
| 240 | + mock_df.write.format.return_value.mode.return_value.save.assert_called_once_with( |
| 241 | + "s3a://bucket/output/" |
| 242 | + ) |
| 243 | + |
| 244 | + def test_persist_raises_without_table_or_path(self, repo_config): |
| 245 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=True) |
| 246 | + storage = SavedDatasetSparkStorage(query="SELECT * FROM t") |
| 247 | + |
| 248 | + with pytest.raises( |
| 249 | + ValueError, match="either 'table' or 'path' must be specified" |
| 250 | + ): |
| 251 | + job.persist(storage) |
| 252 | + |
| 253 | + def test_persist_local_warehouse_creates_temp_view(self, repo_config): |
| 254 | + job = _make_spark_retrieval_job(repo_config, remote_warehouse=False) |
| 255 | + storage = SavedDatasetSparkStorage(table="output_table") |
| 256 | + |
| 257 | + job.persist(storage) |
| 258 | + |
| 259 | + mock_df = job.spark_session.sql.return_value |
| 260 | + mock_df.createOrReplaceTempView.assert_called_once_with("output_table") |
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