SparkGoogleCloudStorageDatasource
SparkGoogleCloudStorageDatasource is a subclass of SparkDatasource which connects to Google Cloud Storage.
Add a csv asset to the datasource.
Add a delta asset to the datasource.
Add a directory_csv asset to the datasource.
Add a directory_delta asset to the datasource.
Add a directory_json asset to the datasource.
Add a directory_orc asset to the datasource.
Add a directory_parquet asset to the datasource.
Add a directory_text asset to the datasource.
Add a json asset to the datasource.
Add an orc asset to the datasource.
Add a parquet asset to the datasource.
Add a text asset to the datasource.
Removes the DataAsset referred to by asset_name from internal list of available DataAsset objects.
Parameters
Name Description name
name of DataAsset to be deleted.
Returns the DataAsset referred to by asset_name
Parameters
Name Description name
name of DataAsset sought.
Returns
Type Description great_expectations.datasource.fluent.interfaces._DataAssetT
if named "DataAsset" object exists; otherwise, exception is raised.
class great_expectations.datasource.fluent.SparkGoogleCloudStorageDatasource(
*,
type: Literal['spark_gcs'] = 'spark_gcs',
name: str,
id: Optional[uuid.UUID] = None,
assets: List[Union[great_expectations.datasource.fluent.data_asset.path.spark.csv_asset.CSVAsset,
great_expectations.datasource.fluent.data_asset.path.spark.csv_asset.DirectoryCSVAsset,
great_expectations.datasource.fluent.data_asset.path.spark.parquet_asset.ParquetAsset,
great_expectations.datasource.fluent.data_asset.path.spark.parquet_asset.DirectoryParquetAsset,
great_expectations.datasource.fluent.data_asset.path.spark.orc_asset.ORCAsset,
great_expectations.datasource.fluent.data_asset.path.spark.orc_asset.DirectoryORCAsset,
great_expectations.datasource.fluent.data_asset.path.spark.json_asset.JSONAsset,
great_expectations.datasource.fluent.data_asset.path.spark.json_asset.DirectoryJSONAsset,
great_expectations.datasource.fluent.data_asset.path.spark.text_asset.TextAsset,
great_expectations.datasource.fluent.data_asset.path.spark.text_asset.DirectoryTextAsset,
great_expectations.datasource.fluent.data_asset.path.spark.delta_asset.DeltaAsset,
great_expectations.datasource.fluent.data_asset.path.spark.delta_asset.DirectoryDeltaAsset]] = [],
spark_config: Optional[Dict[pydantic.v1.types.StrictStr,
Union[pydantic.v1.types.StrictStr,
pydantic.v1.types.StrictInt,
pydantic.v1.types.StrictFloat,
pydantic.v1.types.StrictBool]]] = None,
force_reuse_spark_context: bool = True,
persist: bool = True,
bucket_or_name: str,
gcs_options: Dict[str,
Union[great_expectations.datasource.fluent.config_str.ConfigStr,
Any]] = {}
)
Methods
add_csv_asset
add_csv_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3e629c0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3e62a80> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3e62bd0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3e62d80> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3e62e40> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
schema: typing.Optional[typing.Union[great_expectations.datasource.fluent.serializable_types.pyspark.SerializableStructType,
str]] = None,
sep: typing.Optional[str] = None,
encoding: typing.Optional[str] = None,
quote: typing.Optional[str] = None,
escape: typing.Optional[str] = None,
comment: typing.Optional[str] = None,
header: typing.Optional[typing.Union[bool,
str]] = None,
inferSchema: typing.Optional[typing.Union[bool,
str]] = None,
ignoreLeadingWhiteSpace: typing.Optional[typing.Union[bool,
str]] = None,
ignoreTrailingWhiteSpace: typing.Optional[typing.Union[bool,
str]] = None,
nullValue: typing.Optional[str] = None,
nanValue: typing.Optional[str] = None,
positiveInf: typing.Optional[str] = None,
negativeInf: typing.Optional[str] = None,
dateFormat: typing.Optional[str] = None,
timestampFormat: typing.Optional[str] = None,
maxColumns: typing.Optional[typing.Union[int,
str]] = None,
maxCharsPerColumn: typing.Optional[typing.Union[int,
str]] = None,
maxMalformedLogPerPartition: typing.Optional[typing.Union[int,
str]] = None,
mode: typing.Optional[typing.Literal['PERMISSIVE',
'DROPMALFORMED',
'FAILFAST']] = None,
columnNameOfCorruptRecord: typing.Optional[str] = None,
multiLine: typing.Optional[typing.Union[bool,
str]] = None,
charToEscapeQuoteEscaping: typing.Optional[str] = None,
samplingRatio: typing.Optional[typing.Union[float,
str]] = None,
enforceSchema: typing.Optional[typing.Union[bool,
str]] = None,
emptyValue: typing.Optional[str] = None,
locale: typing.Optional[str] = None,
lineSep: typing.Optional[str] = None,
unescapedQuoteHandling: typing.Optional[typing.Literal['STOP_AT_CLOSING_QUOTE',
'BACK_TO_DELIMITER',
'STOP_AT_DELIMITER',
'SKIP_VALUE',
'RAISE_ERROR']] = None
) → pydantic.BaseModel
add_delta_asset
add_delta_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0a900> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0a9c0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0ab10> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0acc0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0ad80> = None,
timestampAsOf: typing.Optional[str] = None,
versionAsOf: typing.Optional[str] = None
) → pydantic.BaseModel
add_directory_csv_asset
add_directory_csv_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3d09130> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3d091f0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3d09340> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3d094f0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3d095b0> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
schema: typing.Optional[typing.Union[great_expectations.datasource.fluent.serializable_types.pyspark.SerializableStructType,
str]] = None,
sep: typing.Optional[str] = None,
encoding: typing.Optional[str] = None,
quote: typing.Optional[str] = None,
escape: typing.Optional[str] = None,
comment: typing.Optional[str] = None,
header: typing.Optional[typing.Union[bool,
str]] = None,
inferSchema: typing.Optional[typing.Union[bool,
str]] = None,
ignoreLeadingWhiteSpace: typing.Optional[typing.Union[bool,
str]] = None,
ignoreTrailingWhiteSpace: typing.Optional[typing.Union[bool,
str]] = None,
nullValue: typing.Optional[str] = None,
nanValue: typing.Optional[str] = None,
positiveInf: typing.Optional[str] = None,
negativeInf: typing.Optional[str] = None,
dateFormat: typing.Optional[str] = None,
timestampFormat: typing.Optional[str] = None,
maxColumns: typing.Optional[typing.Union[int,
str]] = None,
maxCharsPerColumn: typing.Optional[typing.Union[int,
str]] = None,
maxMalformedLogPerPartition: typing.Optional[typing.Union[int,
str]] = None,
mode: typing.Optional[typing.Literal['PERMISSIVE',
'DROPMALFORMED',
'FAILFAST']] = None,
columnNameOfCorruptRecord: typing.Optional[str] = None,
multiLine: typing.Optional[typing.Union[bool,
str]] = None,
charToEscapeQuoteEscaping: typing.Optional[str] = None,
samplingRatio: typing.Optional[typing.Union[float,
str]] = None,
enforceSchema: typing.Optional[typing.Union[bool,
str]] = None,
emptyValue: typing.Optional[str] = None,
locale: typing.Optional[str] = None,
lineSep: typing.Optional[str] = None,
unescapedQuoteHandling: typing.Optional[typing.Literal['STOP_AT_CLOSING_QUOTE',
'BACK_TO_DELIMITER',
'STOP_AT_DELIMITER',
'SKIP_VALUE',
'RAISE_ERROR']] = None,
data_directory: pathlib.Path
) → pydantic.BaseModel
add_directory_delta_asset
add_directory_delta_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0bb90> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0bc50> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0bda0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3d0bf50> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3d2c050> = None,
timestampAsOf: typing.Optional[str] = None,
versionAsOf: typing.Optional[str] = None,
data_directory: pathlib.Path
) → pydantic.BaseModel
add_directory_json_asset
add_directory_json_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3d51ac0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3d51b80> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3d51cd0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3d51e80> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3d51f40> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
schema: typing.Optional[typing.Union[great_expectations.datasource.fluent.serializable_types.pyspark.SerializableStructType,
str]] = None,
primitivesAsString: typing.Optional[typing.Union[bool,
str]] = None,
prefersDecimal: typing.Optional[typing.Union[bool,
str]] = None,
allowComments: typing.Optional[typing.Union[bool,
str]] = None,
allowUnquotedFieldNames: typing.Optional[typing.Union[bool,
str]] = None,
allowSingleQuotes: typing.Optional[typing.Union[bool,
str]] = None,
allowNumericLeadingZero: typing.Optional[typing.Union[bool,
str]] = None,
allowBackslashEscapingAnyCharacter: typing.Optional[typing.Union[bool,
str]] = None,
mode: typing.Optional[typing.Literal['PERMISSIVE',
'DROPMALFORMED',
'FAILFAST']] = None,
columnNameOfCorruptRecord: typing.Optional[str] = None,
dateFormat: typing.Optional[str] = None,
timestampFormat: typing.Optional[str] = None,
multiLine: typing.Optional[typing.Union[bool,
str]] = None,
allowUnquotedControlChars: typing.Optional[typing.Union[bool,
str]] = None,
lineSep: typing.Optional[str] = None,
samplingRatio: typing.Optional[typing.Union[float,
str]] = None,
dropFieldIfAllNull: typing.Optional[typing.Union[bool,
str]] = None,
encoding: typing.Optional[str] = None,
locale: typing.Optional[str] = None,
allowNonNumericNumbers: typing.Optional[typing.Union[bool,
str]] = None,
data_directory: pathlib.Path
) → pydantic.BaseModel
add_directory_orc_asset
add_directory_orc_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3b79370> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3b79430> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3b79580> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3b79730> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3b797f0> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
mergeSchema: typing.Optional[typing.Union[bool,
str]] = False,
data_directory: pathlib.Path
) → pydantic.BaseModel
add_directory_parquet_asset
add_directory_parquet_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9cec0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9cf80> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9d0d0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9d280> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9d340> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
mergeSchema: typing.Optional[typing.Union[bool,
str]] = None,
datetimeRebaseMode: typing.Optional[typing.Literal['EXCEPTION',
'CORRECTED',
'LEGACY']] = None,
int96RebaseMode: typing.Optional[typing.Literal['EXCEPTION',
'CORRECTED',
'LEGACY']] = None,
data_directory: pathlib.Path
) → pydantic.BaseModel
add_directory_text_asset
add_directory_text_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3bb86b0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3bb8770> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3bb88c0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3bb8a70> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3bb8b30> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
wholetext: bool = False,
lineSep: typing.Optional[str] = None,
data_directory: pathlib.Path
) → pydantic.BaseModel
add_json_asset
add_json_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3d2f3b0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3d2f590> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3d2f740> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3d2f8f0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3d2f9b0> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
schema: typing.Optional[typing.Union[great_expectations.datasource.fluent.serializable_types.pyspark.SerializableStructType,
str]] = None,
primitivesAsString: typing.Optional[typing.Union[bool,
str]] = None,
prefersDecimal: typing.Optional[typing.Union[bool,
str]] = None,
allowComments: typing.Optional[typing.Union[bool,
str]] = None,
allowUnquotedFieldNames: typing.Optional[typing.Union[bool,
str]] = None,
allowSingleQuotes: typing.Optional[typing.Union[bool,
str]] = None,
allowNumericLeadingZero: typing.Optional[typing.Union[bool,
str]] = None,
allowBackslashEscapingAnyCharacter: typing.Optional[typing.Union[bool,
str]] = None,
mode: typing.Optional[typing.Literal['PERMISSIVE',
'DROPMALFORMED',
'FAILFAST']] = None,
columnNameOfCorruptRecord: typing.Optional[str] = None,
dateFormat: typing.Optional[str] = None,
timestampFormat: typing.Optional[str] = None,
multiLine: typing.Optional[typing.Union[bool,
str]] = None,
allowUnquotedControlChars: typing.Optional[typing.Union[bool,
str]] = None,
lineSep: typing.Optional[str] = None,
samplingRatio: typing.Optional[typing.Union[float,
str]] = None,
dropFieldIfAllNull: typing.Optional[typing.Union[bool,
str]] = None,
encoding: typing.Optional[str] = None,
locale: typing.Optional[str] = None,
allowNonNumericNumbers: typing.Optional[typing.Union[bool,
str]] = None
) → pydantic.BaseModel
add_orc_asset
add_orc_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3d53e30> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3d53ef0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3b78080> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3b78230> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3b782f0> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
mergeSchema: typing.Optional[typing.Union[bool,
str]] = False
) → pydantic.BaseModel
add_parquet_asset
add_parquet_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3b7b8c0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3b7b980> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3b7bad0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3b7bc80> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3b7bd40> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
mergeSchema: typing.Optional[typing.Union[bool,
str]] = None,
datetimeRebaseMode: typing.Optional[typing.Literal['EXCEPTION',
'CORRECTED',
'LEGACY']] = None,
int96RebaseMode: typing.Optional[typing.Literal['EXCEPTION',
'CORRECTED',
'LEGACY']] = None
) → pydantic.BaseModel
add_text_asset
add_text_asset(
name: str,
*,
id: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9f170> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9f230> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9f380> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9f530> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7f11a3b9f5f0> = None,
pathGlobFilter: typing.Optional[typing.Union[bool,
str]] = None,
recursiveFileLookup: typing.Optional[typing.Union[bool,
str]] = None,
modifiedBefore: typing.Optional[typing.Union[bool,
str]] = None,
modifiedAfter: typing.Optional[typing.Union[bool,
str]] = None,
wholetext: bool = False,
lineSep: typing.Optional[str] = None
) → pydantic.BaseModel
delete_asset
delete_asset(
name: str
) → None
get_asset
get_asset(
name: str
) → great_expectations.datasource.fluent.interfaces._DataAssetT