Hi,
你需要添加配置，如果你没有使用RocksDB作为statebackend的话，你直接配置t_env.get_config().get_configuration().set_boolean("python.fn-execution.memory.managed",
True)就行，如果你用了的话，就需要配置off-heap
memory了，table_env.get_config().get_configuration().set_string("taskmanager.memory.task.off-heap.size",
'80m')。你可以参考文档上的例子，以及对应的note说明[1][1] https://ci.apache.org/projects/flink/flink-docs-release-1.11/dev/table/python/python_udfs.html#scalar-functions Best, Xingbo chenxuying <[email protected]> 于2020年7月21日周二 上午11:36写道： > 官方例子: > https://flink.apache.org/2020/04/09/pyflink-udf-support-flink.html > 按照例子写了程序,也安装了pyflink > | > python -m pip install apache-flink > | > 代码: > | > from pyflink.datastream import StreamExecutionEnvironment > from pyflink.table import StreamTableEnvironment, DataTypes > from pyflink.table.descriptors import Schema, OldCsv, FileSystem > from pyflink.table.udf import udf > > > env = StreamExecutionEnvironment.get_execution_environment() > env.set_parallelism(1) > t_env = StreamTableEnvironment.create(env) > > > add = udf(lambda i, j: i + j, [DataTypes.BIGINT(), DataTypes.BIGINT()], > DataTypes.BIGINT()) > > > t_env.register_function("add", add) > > > t_env.connect(FileSystem().path('C:/Users/xuyin/Desktop/docker_compose_test/src.txt')) > \ > .with_format(OldCsv() > .field('a', DataTypes.BIGINT()) > .field('b', DataTypes.BIGINT())) \ > .with_schema(Schema() > .field('a', DataTypes.BIGINT()) > .field('b', DataTypes.BIGINT())) \ > .create_temporary_table('mySource') > > > t_env.connect(FileSystem().path('C:/Users/xuyin/Desktop/docker_compose_test/tar.txt')) > \ > .with_format(OldCsv() > .field('sum', DataTypes.BIGINT())) \ > .with_schema(Schema() > .field('sum', DataTypes.BIGINT())) \ > .create_temporary_table('mySink') > > > t_env.from_path('mySource')\ > .select("add(a, b)") \ > .insert_into('mySink') > > > t_env.execute("tutorial_job") > | > > 执行: > > | > python test_pyflink.py > | > > 报错: > > > | > Traceback (most recent call last): > File > "C:\Users\xuyin\AppData\Local\Programs\Python\Python37\lib\site-packages\pyflink\util\exceptions.py", > line 147, in deco > return f(*a, **kw) > File > "C:\Users\xuyin\AppData\Local\Programs\Python\Python37\lib\site-packages\py4j\protocol.py", > line 328, in get_return_value > format(target_id, ".", name), value) > py4j.protocol.Py4JJavaError: An error occurred while calling o2.execute. > : org.apache.flink.table.api.TableException: The configured Task Off-Heap > Memory 0 bytes is less than the least required Python worker Memory 79 mb. > The Task Off-Heap Memory can be configured using the configuration key > 'taskmanager.memory.task.off-heap.size'. > at > org.apache.flink.table.planner.plan.nodes.common.CommonPythonBase$class.checkPythonWorkerMemory(CommonPythonBase.scala:158) > at > org.apache.flink.table.planner.plan.nodes.common.CommonPythonBase$class.getMergedConfiguration(CommonPythonBase.scala:119) > at > org.apache.flink.table.planner.plan.nodes.common.CommonPythonBase$class.getConfig(CommonPythonBase.scala:102) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecPythonCalc.getConfig(StreamExecPythonCalc.scala:35) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecPythonCalc.translateToPlanInternal(StreamExecPythonCalc.scala:61) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecPythonCalc.translateToPlanInternal(StreamExecPythonCalc.scala:35) > at > org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:58) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecCalcBase.translateToPlan(StreamExecCalcBase.scala:38) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecLegacySink.translateToTransformation(StreamExecLegacySink.scala:158) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecLegacySink.translateToPlanInternal(StreamExecLegacySink.scala:106) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecLegacySink.translateToPlanInternal(StreamExecLegacySink.scala:48) > at > org.apache.flink.table.planner.plan.nodes.exec.ExecNode$class.translateToPlan(ExecNode.scala:58) > at > org.apache.flink.table.planner.plan.nodes.physical.stream.StreamExecLegacySink.translateToPlan(StreamExecLegacySink.scala:48) > at > org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:67) > at > org.apache.flink.table.planner.delegation.StreamPlanner$$anonfun$translateToPlan$1.apply(StreamPlanner.scala:66) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at > scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234) > at scala.collection.Iterator$class.foreach(Iterator.scala:891) > at scala.collection.AbstractIterator.foreach(Iterator.scala:1334) > at > scala.collection.IterableLike$class.foreach(IterableLike.scala:72) > at scala.collection.AbstractIterable.foreach(Iterable.scala:54) > at > scala.collection.TraversableLike$class.map(TraversableLike.scala:234) > at scala.collection.AbstractTraversable.map(Traversable.scala:104) > at > org.apache.flink.table.planner.delegation.StreamPlanner.translateToPlan(StreamPlanner.scala:66) > at > org.apache.flink.table.planner.delegation.PlannerBase.translate(PlannerBase.scala:166) > at > org.apache.flink.table.api.internal.TableEnvironmentImpl.translate(TableEnvironmentImpl.java:1248) > at > org.apache.flink.table.api.internal.TableEnvironmentImpl.translateAndClearBuffer(TableEnvironmentImpl.java:1240) > at > org.apache.flink.table.api.internal.TableEnvironmentImpl.execute(TableEnvironmentImpl.java:1197) > at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) > at > sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) > at > sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) > at java.lang.reflect.Method.invoke(Method.java:497) > at > org.apache.flink.api.python.shaded.py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244) > at > org.apache.flink.api.python.shaded.py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357) > at > org.apache.flink.api.python.shaded.py4j.Gateway.invoke(Gateway.java:282) > at > org.apache.flink.api.python.shaded.py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132) > at > org.apache.flink.api.python.shaded.py4j.commands.CallCommand.execute(CallCommand.java:79) > at > org.apache.flink.api.python.shaded.py4j.GatewayConnection.run(GatewayConnection.java:238) > at java.lang.Thread.run(Thread.java:745) > > > > > During handling of the above exception, another exception occurred: > > > Traceback (most recent call last): > File "test_pyflink.py", line 34, in <module> > t_env.execute("tutorial_job") > File > "C:\Users\xuyin\AppData\Local\Programs\Python\Python37\lib\site-packages\pyflink\table\table_environment.py", > line 1057, in execute > return JobExecutionResult(self._j_tenv.execute(job_name)) > File > "C:\Users\xuyin\AppData\Local\Programs\Python\Python37\lib\site-packages\py4j\java_gateway.py", > line 1286, in __call__ > answer, self.gateway_client, self.target_id, self.name) > File > "C:\Users\xuyin\AppData\Local\Programs\Python\Python37\lib\site-packages\pyflink\util\exceptions.py", > line 154, in deco > raise exception_mapping[exception](s.split(': ', 1)[1], stack_trace) > pyflink.util.exceptions.TableException: "The configured Task Off-Heap > Memory 0 bytes is less than the least required Python worker Memory 79 mb. > The Task Off-Heap Memory can be configured using the configuration key > 'taskmanager.memory.task.off-heap.size'." > | > > > > > 里面提到还要配置taskmanager.memory.task.off-heap.size这个属性吗 , > > 我找到..\Python\Python37\Lib\site-packages\pyflink\conf下面的flink-conf.yaml > > 增加了taskmanager.memory.task.off-heap.size: 100m > > 但是还是报一样的错误 > > 请问用python安装的flink去哪里配置属性 > > >
