MINOR: Add support for csv.gz in datalake (#22666)

* MINOR: Add support for csv.gz in datalake

* fileformat change

* Update generated TypeScript types

* pyformat

ingestion/src/metadata/readers/dataframe/dsv.py

@@ -54,16 +54,24 @@ class DSVDataFrameReader(DataFrameReader):
         super().__init__(config_source, client)
 
     def read_from_pandas(
-        self, path: str, storage_options: Optional[Dict[str, Any]] = None
+        self,
+        path: str,
+        storage_options: Optional[Dict[str, Any]] = None,
+        compression: Optional[str] = None,
     ) -> DatalakeColumnWrapper:
         import pandas as pd  # pylint: disable=import-outside-toplevel
 
+        # Determine compression based on file extension if not provided
+        if compression is None and path.endswith(".gz"):
+            compression = "gzip"
+
         chunk_list = []
         with pd.read_csv(
             path,
             sep=self.separator,
             chunksize=CHUNKSIZE,
             storage_options=storage_options,
+            compression=compression,
         ) as reader:
             for chunks in reader:
                 chunk_list.append(chunks)
@@ -81,16 +89,47 @@ class DSVDataFrameReader(DataFrameReader):
         """
         Read the CSV file from the gcs bucket and return a dataframe
         """
+        # Determine compression based on file extension
+        compression = None
+        if key.endswith(".gz"):
+            compression = "gzip"
+
         path = f"gs://{bucket_name}/{key}"
-        return self.read_from_pandas(path=path)
+        return self.read_from_pandas(path=path, compression=compression)
 
     @_read_dsv_dispatch.register
     def _(self, _: S3Config, key: str, bucket_name: str) -> DatalakeColumnWrapper:
-        path = self.client.get_object(Bucket=bucket_name, Key=key)["Body"]
-        return self.read_from_pandas(path=path)
+        import pandas as pd  # pylint: disable=import-outside-toplevel
+
+        # Determine compression based on file extension
+        compression = None
+        if key.endswith(".gz"):
+            compression = "gzip"
+
+        # Get the file content from S3
+        response = self.client.get_object(Bucket=bucket_name, Key=key)
+        file_content = response["Body"]
+
+        # Read the CSV data directly from the StreamingBody
+        chunk_list = []
+        with pd.read_csv(
+            file_content,
+            sep=self.separator,
+            chunksize=CHUNKSIZE,
+            compression=compression,
+        ) as reader:
+            for chunks in reader:
+                chunk_list.append(chunks)
+
+        return DatalakeColumnWrapper(dataframes=chunk_list)
 
     @_read_dsv_dispatch.register
     def _(self, _: AzureConfig, key: str, bucket_name: str) -> DatalakeColumnWrapper:
+        # Determine compression based on file extension
+        compression = None
+        if key.endswith(".gz"):
+            compression = "gzip"
+
         storage_options = return_azure_storage_options(self.config_source)
         path = AZURE_PATH.format(
             bucket_name=bucket_name,
@@ -100,13 +139,19 @@ class DSVDataFrameReader(DataFrameReader):
         return self.read_from_pandas(
             path=path,
             storage_options=storage_options,
+            compression=compression,
         )
 
     @_read_dsv_dispatch.register
     def _(  # pylint: disable=unused-argument
         self, _: LocalConfig, key: str, bucket_name: str
     ) -> DatalakeColumnWrapper:
-        return self.read_from_pandas(path=key)
+        # Determine compression based on file extension
+        compression = None
+        if key.endswith(".gz"):
+            compression = "gzip"
+
+        return self.read_from_pandas(path=key, compression=compression)
 
     def _read(self, *, key: str, bucket_name: str, **__) -> DatalakeColumnWrapper:
         return self._read_dsv_dispatch(

ingestion/src/metadata/readers/dataframe/reader_factory.py

@@ -36,6 +36,7 @@ logger = utils_logger()
 
 class SupportedTypes(Enum):
     CSV = "csv"
+    CSVGZ = "csv.gz"
     TSV = "tsv"
     AVRO = "avro"
     PARQUET = "parquet"
@@ -53,6 +54,7 @@ class SupportedTypes(Enum):
 
 DF_READER_MAP = {
     SupportedTypes.CSV.value: CSVDataFrameReader,
+    SupportedTypes.CSVGZ.value: CSVDataFrameReader,
     SupportedTypes.TSV.value: TSVDataFrameReader,
     SupportedTypes.AVRO.value: AvroDataFrameReader,
     SupportedTypes.PARQUET.value: ParquetDataFrameReader,
@@ -79,7 +81,10 @@ def get_df_reader(
     Load the File Reader based on the Config Source
     """
     # If we have a DSV file, build a reader dynamically based on the received separator
-    if type_ in {SupportedTypes.CSV, SupportedTypes.TSV} and separator:
+    if (
+        type_ in {SupportedTypes.CSV, SupportedTypes.CSVGZ, SupportedTypes.TSV}
+        and separator
+    ):
         return get_dsv_reader_by_separator(separator=separator)(
             config_source=config_source, client=client
         )

ingestion/src/metadata/utils/datalake/datalake_utils.py

@@ -66,6 +66,7 @@ def fetch_dataframe(
                     return df_wrapper.dataframes, df_wrapper.raw_data
                 return df_wrapper.dataframes
             except Exception as err:
+                logger.debug(traceback.format_exc())
                 logger.error(
                     f"Error fetching file [{bucket_name}/{key}] using "
                     f"[{config_source.__class__.__name__}] due to: [{err}]"

ingestion/tests/unit/utils/test_datalake.py

@@ -23,6 +23,7 @@ from metadata.utils.datalake.datalake_utils import (
     DataFrameColumnParser,
     GenericDataFrameColumnParser,
     ParquetDataFrameColumnParser,
+    get_file_format_type,
 )
 
 STRUCTURE = {
@@ -451,3 +452,141 @@ class TestParquetDataFrameColumnParser(TestCase):
                 with self.subTest(validation=validation):
                     expected_col, actual_col = validation
                     self._validate_parsed_column(expected_col, actual_col)
+
+    def test_get_file_format_type_csv_gz(self):
+        """test get_file_format_type function for csv.gz files"""
+        # Test csv.gz file detection
+        result = get_file_format_type("data.csv.gz")
+        self.assertEqual(result, SupportedTypes.CSVGZ)
+
+        # Test regular csv file detection (should still work)
+        result = get_file_format_type("data.csv")
+        self.assertEqual(result, SupportedTypes.CSV)
+
+        # Test other gzipped files
+        result = get_file_format_type("data.json.gz")
+        self.assertEqual(result, SupportedTypes.JSONGZ)
+
+        # Test unsupported gzipped format
+        result = get_file_format_type("data.txt.gz")
+        self.assertEqual(result, False)
+
+    def test_csv_gz_file_format_detection_edge_cases(self):
+        """test edge cases for csv.gz file format detection"""
+        # Test with nested paths
+        result = get_file_format_type("folder/subfolder/data.csv.gz")
+        self.assertEqual(result, SupportedTypes.CSVGZ)
+
+        # Test with multiple dots
+        result = get_file_format_type("data.backup.csv.gz")
+        self.assertEqual(result, SupportedTypes.CSVGZ)
+
+        # Test with no extension
+        result = get_file_format_type("data")
+        self.assertEqual(result, False)
+
+        # Test with just .gz
+        result = get_file_format_type("data.gz")
+        self.assertEqual(result, False)
+
+    def test_csv_gz_compression_detection(self):
+        """test compression detection for various file types"""
+        # Test csv.gz compression detection
+        test_cases = [
+            ("data.csv.gz", SupportedTypes.CSVGZ),
+            ("data.csv", SupportedTypes.CSV),
+            ("data.json.gz", SupportedTypes.JSONGZ),
+            ("data.json", SupportedTypes.JSON),
+            ("data.jsonl.gz", SupportedTypes.JSONLGZ),
+            ("data.jsonl", SupportedTypes.JSONL),
+            ("data.parquet", SupportedTypes.PARQUET),
+            ("data.txt.gz", False),  # Unsupported
+            ("data.unknown.gz", False),  # Unsupported
+        ]
+
+        for filename, expected in test_cases:
+            with self.subTest(filename=filename):
+                result = get_file_format_type(filename)
+                self.assertEqual(result, expected, f"Failed for {filename}")
+
+    def test_csv_gz_reader_factory_integration(self):
+        """test that csv.gz is properly integrated with reader factory"""
+        from metadata.readers.dataframe.reader_factory import SupportedTypes
+
+        # Test that CSVGZ is properly handled
+        try:
+            # Test that the enum value exists
+            self.assertEqual(SupportedTypes.CSVGZ.value, "csv.gz")
+
+            # Test that it's different from regular CSV
+            self.assertNotEqual(SupportedTypes.CSVGZ, SupportedTypes.CSV)
+            self.assertNotEqual(SupportedTypes.CSVGZ.value, SupportedTypes.CSV.value)
+
+        except Exception as e:
+            self.fail(f"CSVGZ enum test failed: {e}")
+
+    def test_csv_gz_supported_types_enum(self):
+        """test that CSVGZ is properly defined in SupportedTypes enum"""
+        # Test that CSVGZ exists in the enum
+        self.assertIn(SupportedTypes.CSVGZ, SupportedTypes)
+        self.assertEqual(SupportedTypes.CSVGZ.value, "csv.gz")
+
+        # Test that it's different from regular CSV
+        self.assertNotEqual(SupportedTypes.CSVGZ, SupportedTypes.CSV)
+        self.assertNotEqual(SupportedTypes.CSVGZ.value, SupportedTypes.CSV.value)
+
+    def test_csv_gz_dsv_reader_compression_detection(self):
+        """test that DSV reader properly detects compression for csv.gz files"""
+        from metadata.generated.schema.entity.services.connections.database.datalakeConnection import (
+            LocalConfig,
+        )
+        from metadata.readers.dataframe.dsv import DSVDataFrameReader
+
+        # Create a mock config
+        local_config = LocalConfig()
+
+        # Create DSV reader
+        reader = DSVDataFrameReader(config_source=local_config, client=None)
+
+        # Test compression detection logic (this is the same logic used in the dispatch methods)
+        test_cases = [
+            ("data.csv.gz", "gzip"),
+            ("data.csv", None),
+            ("data.json.gz", "gzip"),
+            ("data.txt.gz", "gzip"),
+            ("data.unknown.gz", "gzip"),
+        ]
+
+        for filename, expected_compression in test_cases:
+            with self.subTest(filename=filename):
+                # Simulate the compression detection logic from the dispatch methods
+                compression = None
+                if filename.endswith(".gz"):
+                    compression = "gzip"
+
+                self.assertEqual(
+                    compression,
+                    expected_compression,
+                    f"Compression detection failed for {filename}",
+                )
+
+    def test_csv_gz_integration_completeness(self):
+        """test that csv.gz support is complete across all components"""
+        # Test that CSVGZ is in the reader factory mapping
+        from metadata.readers.dataframe.reader_factory import (
+            DF_READER_MAP,
+            SupportedTypes,
+        )
+
+        # Check that CSVGZ is mapped to CSVDataFrameReader
+        self.assertIn(SupportedTypes.CSVGZ.value, DF_READER_MAP)
+
+        # Test that the get_df_reader function includes CSVGZ in DSV handling
+
+        # This should not raise an exception for CSVGZ
+        try:
+            # Test that CSVGZ is included in the DSV types
+            dsv_types = {SupportedTypes.CSV, SupportedTypes.CSVGZ, SupportedTypes.TSV}
+            self.assertIn(SupportedTypes.CSVGZ, dsv_types)
+        except Exception as e:
+            self.fail(f"CSVGZ integration test failed: {e}")

openmetadata-spec/src/main/resources/json/schema/entity/data/table.json

@@ -996,7 +996,7 @@
     "fileFormat": {
       "description": "File format in case of file/datalake tables.",
       "type": "string",
-      "enum": ["csv", "tsv", "avro", "parquet", "pq", "pqt", "parq", "parquet.snappy", "json", "json.gz", "json.zip", "jsonl", "jsonl.gz", "jsonl.zip"]
+      "enum": ["csv", "csv.gz", "tsv", "avro", "parquet", "pq", "pqt", "parq", "parquet.snappy", "json", "json.gz", "json.zip", "jsonl", "jsonl.gz", "jsonl.zip"]
     }
   },
   "properties": {

openmetadata-ui/src/main/resources/ui/src/generated/api/data/createTable.ts

@@ -668,6 +668,7 @@ export enum ModelType {
 export enum FileFormat {
     Avro = "avro",
     CSV = "csv",
+    CSVGz = "csv.gz",
     JSON = "json",
     JSONGz = "json.gz",
     JSONZip = "json.zip",

openmetadata-ui/src/main/resources/ui/src/generated/entity/data/table.ts

@@ -867,6 +867,7 @@ export enum ModelType {
 export enum FileFormat {
     Avro = "avro",
     CSV = "csv",
+    CSVGz = "csv.gz",
     JSON = "json",
     JSONGz = "json.gz",
     JSONZip = "json.zip",