SparkS3Datasource
SparkS3Datasource is a subclass of SparkDatasource which connects to Amazon S3.
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.SparkS3Datasource(
*,
type: Literal['spark_s3'] = 'spark_s3',
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: str,
boto3_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 0x7ff25b99ac30> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b99acf0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b99ae40> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b99aff0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b99b0b0> = 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 0x7ff25b7eeba0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b7eec60> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b7eedb0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b7eef60> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b7ef020> = 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 0x7ff25b7ed370> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b7ed430> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b7ed580> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b7ed730> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b7ed7f0> = 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 0x7ff25b7efe30> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b7efef0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b800080> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b800230> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b8002f0> = 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 0x7ff25b835d60> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b835e20> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b835f70> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b836120> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b8361e0> = 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 0x7ff25b8515e0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b8516a0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b8517f0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b8519a0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b851a60> = 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 0x7ff25b871130> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b8711f0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b871340> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b8714f0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b8715b0> = 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 0x7ff25b888950> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b888a10> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b888b60> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b888d10> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b888dd0> = 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 0x7ff25b803740> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b803890> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b8039e0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b803b90> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b803c50> = 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 0x7ff25b8500b0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b850170> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b8502c0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b850470> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b850530> = 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 0x7ff25b853b30> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b853bf0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b853d40> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b853ef0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b853fb0> = 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 0x7ff25b8733e0> = None,
order_by: <pydantic.v1.fields.DeferredType object at 0x7ff25b8734a0> = None,
batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7ff25b8735f0> = None,
batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7ff25b8737a0> = None,
connect_options: <pydantic.v1.fields.DeferredType object at 0x7ff25b873860> = 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