select([col for col in df.columns if col != "team"]) Powered By Complex conditions with .selectExpr() If we're comfortable with SQL and need to apply more complex conditions when filtering columns, PySpark's .selectExpr() method offers a powerful solution. It allows us to use SQL-...
First you're going to set up a simple Spark Streaming job to generate a sequence and make the job write to your Delta Table.Python คัดลอก streaming_df = spark.readStream.format("rate").load() stream = streaming_df\ .selectExpr("value as id")...
select([col for col in df.columns if col != "team"]) Powered By Complex conditions with .selectExpr() If we're comfortable with SQL and need to apply more complex conditions when filtering columns, PySpark's .selectExpr() method offers a powerful solution. It allows us to use SQL-...
First you're going to set up a simple Spark Streaming job to generate a sequence and make the job write to your Delta Table. Python streaming_df = spark.readStream.format("rate").load() stream = streaming_df\ .selectExpr("value as id")\ .writeStream\ .format(...