各位大佬,我想尝试下pyflink 进行时间窗口下的指标统计,写了一个demo发现table APi 的group 方法报错,网上搜索了一下相关内容也没有解决问题, 想请各位大佬帮帮忙看一下是哪里写错了?
错误信息: py4j.protocol.Py4JJavaError: An error occurred while calling o95.select. : org.apache.flink.table.api.ValidationException: A group window expects a time attribute for grouping in a stream environment. at org.apache.flink.table.operations.utils.AggregateOperationFactory.validateStreamTimeAttribute(AggregateOperationFactory.java:293) at org.apache.flink.table.operations.utils.AggregateOperationFactory.validateTimeAttributeType(AggregateOperationFactory.java:278) at org.apache.flink.table.operations.utils.AggregateOperationFactory.getValidatedTimeAttribute(AggregateOperationFactory.java:271) at org.apache.flink.table.operations.utils.AggregateOperationFactory.createResolvedWindow(AggregateOperationFactory.java:233) at org.apache.flink.table.operations.utils.OperationTreeBuilder.windowAggregate(OperationTreeBuilder.java:250) at org.apache.flink.table.api.internal.TableImpl$WindowGroupedTableImpl.select(TableImpl.java:794) at org.apache.flink.table.api.internal.TableImpl$WindowGroupedTableImpl.select(TableImpl.java:781) demo程序: from pyflink.datastream import * from pyflink.table import * from pyflink.table.descriptors import * from pyflink.table.descriptors import Json from pyflink.table.window import * test_out_put_data_path = r'D:\test_doc\test_result_data.csv' s_nev = StreamExecutionEnvironment.get_execution_environment() s_nev.set_parallelism(3) st_nev = StreamTableEnvironment.create(s_nev, environment_settings=EnvironmentSettings.new_instance().in_streaming_mode().use_blink_planner().build()) st_nev.connect(Kafka().version('0.11').topic('gyhWebLog').start_from_earliest().property("zookeeper.connect","cdh3:2181, cdh4:2181, cdh5:2181").property("bootstrap.servers", "cdh3:9092, cdh4:9092, cdh5:9092")) \ .with_format(Json() .fail_on_missing_field(False) .schema(DataTypes.ROW([DataTypes.FIELD('time', DataTypes.TIMESTAMP(3)), DataTypes.FIELD('prev_page',DataTypes.STRING()), DataTypes.FIELD('page', DataTypes.STRING()), DataTypes.FIELD("app", DataTypes.STRING()), DataTypes.FIELD("nextApp",DataTypes.STRING()), DataTypes.FIELD("service",DataTypes.STRING()), DataTypes.FIELD("userId",DataTypes.BIGINT())])))\ .with_schema(Schema(). field('prev_page', DataTypes.STRING()) .field('page', DataTypes.STRING()) .field('app', DataTypes.STRING()) .field('nextApp', DataTypes.STRING()) .field('service', DataTypes.STRING()) .field('userId', DataTypes.BIGINT()) .field('time', DataTypes.TIMESTAMP(3)) .rowtime(Rowtime() .timestamps_from_field('time') .watermarks_periodic_bounded(60000)))\ .in_append_mode()\ .create_temporary_table('raw_web_log_data') st_nev.connect(FileSystem().path(test_out_put_data_path))\ .with_format(OldCsv() .field_delimiter(',') .field("userId", DataTypes.BIGINT()) .field('dataCount', DataTypes.BIGINT()) .field('count_time', DataTypes.TIMESTAMP(3)) )\ .with_schema(Schema() .field('userId', DataTypes.BIGINT()) .field('dataCount', DataTypes.BIGINT()) .field('count_time', DataTypes.TIMESTAMP(3)) )\ .create_temporary_table('test_out_put') if __name__ == '__main__': st_nev.from_path('raw_web_log_data').window(Tumble.over('1.hours').on('time').alias('w')).group_by('userId, w').select('userId, page.count as d, w.end').execute_insert('test_out_put')