SparkS3Datasource

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]] = )#

SparkS3Datasource is a subclass of SparkDatasource which connects to Amazon S3.

Methods

add_csv_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bcea6b4a0> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bcea6b560> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bcea6b6b0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bcea6b860> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bcea6b920> = 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 a csv asset to the datasource.

add_delta_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bceac3440> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bceac3500> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bceac3650> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bceac3800> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bceac38c0> = None, timestampAsOf: typing.Optional[str] = None, versionAsOf: typing.Optional[str] = None) → pydantic.BaseModel#

Add a delta asset to the datasource.

add_directory_csv_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bceac1be0> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bceac1ca0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bceac1df0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bceac1fa0> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bceac2060> = 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 a directory_csv asset to the datasource.

add_directory_delta_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce8e06e0> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce8e07a0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce8e08f0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce8e0aa0> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce8e0b60> = None, timestampAsOf: typing.Optional[str] = None, versionAsOf: typing.Optional[str] = None, data_directory: pathlib.Path) → pydantic.BaseModel#

Add a directory_delta asset to the datasource.

add_directory_json_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fe630> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fe6f0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fe840> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fe9f0> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce8feab0> = 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 a directory_json asset to the datasource.

add_directory_orc_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce925a30> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce925af0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce925700> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce9259d0> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce925a60> = 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 a directory_orc asset to the datasource.

add_directory_parquet_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce926810> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce926900> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce9268d0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce926840> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce926240> = 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 a directory_parquet asset to the datasource.

add_directory_text_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce9276e0> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce927740> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce927620> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce927500> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce927710> = 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 a directory_text asset to the datasource.

add_json_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce8e3e90> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fc1a0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fc2f0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fc4a0> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce8fc560> = 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 a json asset to the datasource.

add_orc_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce9249b0> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce924a70> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce924bc0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce924d70> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce924e30> = 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 an orc asset to the datasource.

add_parquet_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce925fa0> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce9264e0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce9264b0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce926420> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce926300> = 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 a parquet asset to the datasource.

add_text_asset(name: str, *, id: <pydantic.v1.fields.DeferredType object at 0x7f0bce927080> = None, order_by: <pydantic.v1.fields.DeferredType object at 0x7f0bce9270e0> = None, batch_metadata: <pydantic.v1.fields.DeferredType object at 0x7f0bce926fc0> = None, batch_definitions: <pydantic.v1.fields.DeferredType object at 0x7f0bce926ed0> = None, connect_options: <pydantic.v1.fields.DeferredType object at 0x7f0bce9270b0> = 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#

Add a text asset to the datasource.

delete_asset(name: str)→ None#

Removes the DataAsset referred to by asset_name from internal list of available DataAsset objects.

Parameters

name – name of DataAsset to be deleted.

get_asset(name: str)→ great_expectations.datasource.fluent.interfaces._DataAssetT#

Returns the DataAsset referred to by asset_name

Parameters

name – name of DataAsset sought.

Returns

_DataAssetT – if named “DataAsset” object exists; otherwise, exception is raised.