implicit class DatasetConfOperations extends AnyRef
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- new DatasetConfOperations(ds: DatasetConf)
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def
read(implicit config: Configuration, spark: SparkSession): DataFrame
Using an instance of Spark and the current configuration, reads the dataset from either the tableName or from the location.
Using an instance of Spark and the current configuration, reads the dataset from either the tableName or from the location.
- config
configuration currently loaded
- spark
instance of SparkSession
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def
readCurrent(implicit config: Configuration, spark: SparkSession): DataFrame
Read current version of a given DatasetConf based on its loadType
Read current version of a given DatasetConf based on its loadType
- config
configuration currently loaded
- spark
instance of SparkSession
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def
replacePath(pattern: String, replacement: String): DatasetConf
Replace the substrings matching the pattern with the replacement value in the path.
Replace the substrings matching the pattern with the replacement value in the path.
- pattern
The sequence to be replaced
- replacement
The replacement sequence
- returns
A new DatasetConf with its path updated
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def
replacePlaceholders(placeholder: String, replacement: String): DatasetConf
Replace the placeholders in the DatasetConf with the replacement value.
Replace the placeholders in the DatasetConf with the replacement value. The replacement value will be cleaned before being used in the table name. Valid table names only contain alphabet characters, numbers and _. All invalid characters will be replaced by an _.
- placeholder
The placeholder value to be replaced
- replacement
The replacement sequence
- returns
A new DatasetConf with its placeholders filled
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def
replaceTableName(pattern: String, replacement: String, clean: Boolean): DatasetConf
Replace the substrings matching the pattern with the replacement value in the table name.
Replace the substrings matching the pattern with the replacement value in the table name. Valid table names only contain alphabet characters, numbers and _. If clean is set to true, all invalid characters will be replaced by an _. The method will not fail when using a replacement value with invalid characters, but Spark might fail later when trying to create the table.
- pattern
The sequence to be replaced
- replacement
The replacement sequence
- clean
If true, cleans the replacement sequence
- returns
A new DatasetConf with its table name updated
- def resetTo(dateTime: LocalDateTime)(implicit config: Configuration, spark: SparkSession): Unit
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