PySpark is a powerful tool for processing large datasets in Python. One common task when working with data in PySpark is changing the data types of columns. This could be necessary for various reasons, such as converting a string column to an integer column for mathematical operations, or chang...
PySpark In PySpark, we can use the cast method to change the data type. frompyspark.sql.typesimportIntegerTypefrompyspark.sqlimportfunctionsasF# first methoddf = df.withColumn("Age", df.age.cast("int"))# second methoddf = df.withColumn("Age", df.age.cast(IntegerType()))# third methodd...
We can change the column name in the PySpark DataFrame using this method. Syntax: dataframe.withColumnRenamed(“old_column “,”new_column”) Parameters: old_column is the existing column new_column is the new column that replaces the old_column Example: In this example, we are replacing the...
def castColumnTo( df: DataFrame, cn: String, type: DataType ) : DataFrame = { df.withColumn( cn, df(cn).cast(type) ) } } which is used like: import DFHelper._ val df2 = castColumnTo( df, "year", IntegerType ) If you want to know more regarding spark, you can refer the fo...
Update our ‘DeletedFlag’ column for rows that have been deleted. There are multiple methods to manage changes, and each organization or data model has unique requirements. Whether there’s a need to entirely overwrite values without retaining history, establish a type-2 slowly changing ...
Process SCD type 2 updates The following example demonstrates processing SCD type 2 updates: Python SQL importdltfrompyspark.sql.functionsimportcol,expr@dlt.viewdefusers():returnspark.readStream.table("cdc_data.users")dlt.create_streaming_table("target")dlt.apply_changes(target="target",source="us...
You can create an `AutoTSTrainer` as follows (`dt_col` is the datetime, `target_col` is the target column, and `extra_features_col` is the extra features): ```python from zoo.zouwu.autots.forecast import AutoTSTrainer from zoo.chronos.autots.forecast import AutoTSTrainer trainer = AutoT...
The error message you are getting is because you are trying to insert a column into the target table that does not exist in the source table. This is not allowed by Delta Lake, because it could corrupt the data in the target table. ...
Process SCD type 1 updates The following example demonstrates processing SCD type 1 updates: Python Python importdltfrompyspark.sql.functionsimportcol, expr@dlt.viewdefusers():returnspark.readStream.table("cdc_data.users") dlt.create_streaming_table("target") dlt.apply_changes( target ="target",...
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