windowedCounts3 = words \ .filter("content like '%error%'") # 开始运行查询并在控制台输出 query = windowedCounts3 \ .writeStream \ .outputMode("update") \ .format("console") \ .option('truncate', 'false')\ .trigger(processingTime="3 seconds") \ .start() query.awaitTermination()

This code snippet is using PySpark's Structured Streaming API to perform a query on a stream of data. The `words` stream is being filtered using the `filter` transformation to only include records where the `content` attribute contains the word "error".

The resulting stream is then written to the console using the `writeStream` method. The output mode is set to "update", which means that only the changed data will be output to the console. The `truncate` option is set to "false", which means that the full contents of each record will be displayed in the console. The trigger is set to run every 3 seconds using the `processingTime` option.

Finally, the query is started using the `start` method and the `awaitTermination` method is called to keep the query running until it is manually stopped.