pyflink1.11 window groupby出错

[刘乘九]

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')