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| ################################################################################ |
| |
| ========================== |
| StreamExecutionEnvironment |
| ========================== |
| |
| StreamExecutionEnvironment |
| -------------------------- |
| |
| The StreamExecutionEnvironment is the context in which a streaming program is executed. A |
| *LocalStreamEnvironment* will cause execution in the attached JVM, a |
| *RemoteStreamEnvironment* will cause execution on a remote setup. |
| |
| The environment provides methods to control the job execution (such as setting the parallelism |
| or the fault tolerance/checkpointing parameters) and to interact with the outside world (data |
| access). |
| |
| .. currentmodule:: pyflink.datastream.stream_execution_environment |
| |
| .. autosummary:: |
| :toctree: api/ |
| |
| StreamExecutionEnvironment.get_config |
| StreamExecutionEnvironment.set_parallelism |
| StreamExecutionEnvironment.set_max_parallelism |
| StreamExecutionEnvironment.register_slot_sharing_group |
| StreamExecutionEnvironment.get_parallelism |
| StreamExecutionEnvironment.get_max_parallelism |
| StreamExecutionEnvironment.set_runtime_mode |
| StreamExecutionEnvironment.set_buffer_timeout |
| StreamExecutionEnvironment.get_buffer_timeout |
| StreamExecutionEnvironment.disable_operator_chaining |
| StreamExecutionEnvironment.is_chaining_enabled |
| StreamExecutionEnvironment.get_checkpoint_config |
| StreamExecutionEnvironment.enable_checkpointing |
| StreamExecutionEnvironment.get_checkpoint_interval |
| StreamExecutionEnvironment.get_checkpointing_mode |
| StreamExecutionEnvironment.get_state_backend |
| StreamExecutionEnvironment.set_state_backend |
| StreamExecutionEnvironment.enable_changelog_state_backend |
| StreamExecutionEnvironment.is_changelog_state_backend_enabled |
| StreamExecutionEnvironment.set_default_savepoint_directory |
| StreamExecutionEnvironment.get_default_savepoint_directory |
| StreamExecutionEnvironment.set_restart_strategy |
| StreamExecutionEnvironment.get_restart_strategy |
| StreamExecutionEnvironment.add_default_kryo_serializer |
| StreamExecutionEnvironment.register_type_with_kryo_serializer |
| StreamExecutionEnvironment.register_type |
| StreamExecutionEnvironment.set_stream_time_characteristic |
| StreamExecutionEnvironment.get_stream_time_characteristic |
| StreamExecutionEnvironment.configure |
| StreamExecutionEnvironment.add_python_file |
| StreamExecutionEnvironment.set_python_requirements |
| StreamExecutionEnvironment.add_python_archive |
| StreamExecutionEnvironment.set_python_executable |
| StreamExecutionEnvironment.add_jars |
| StreamExecutionEnvironment.add_classpaths |
| StreamExecutionEnvironment.get_default_local_parallelism |
| StreamExecutionEnvironment.set_default_local_parallelism |
| StreamExecutionEnvironment.execute |
| StreamExecutionEnvironment.execute_async |
| StreamExecutionEnvironment.get_execution_plan |
| StreamExecutionEnvironment.register_cached_file |
| StreamExecutionEnvironment.get_execution_environment |
| StreamExecutionEnvironment.create_input |
| StreamExecutionEnvironment.add_source |
| StreamExecutionEnvironment.from_source |
| StreamExecutionEnvironment.read_text_file |
| StreamExecutionEnvironment.from_collection |
| StreamExecutionEnvironment.is_unaligned_checkpoints_enabled |
| StreamExecutionEnvironment.is_force_unaligned_checkpoints |
| StreamExecutionEnvironment.close |
| |
| |
| RuntimeExecutionMode |
| -------------------- |
| |
| Runtime execution mode of DataStream programs. Among other things, this controls task |
| scheduling, network shuffle behavior, and time semantics. Some operations will also change |
| their record emission behaviour based on the configured execution mode. |
| |
| :data:`STREAMING`: |
| |
| The Pipeline will be executed with Streaming Semantics. All tasks will be deployed before |
| execution starts, checkpoints will be enabled, and both processing and event time will be |
| fully supported. |
| |
| :data:`BATCH`: |
| |
| The Pipeline will be executed with Batch Semantics. Tasks will be scheduled gradually based |
| on the scheduling region they belong, shuffles between regions will be blocking, watermarks |
| are assumed to be "perfect" i.e. no late data, and processing time is assumed to not advance |
| during execution. |
| |
| :data:`AUTOMATIC`: |
| |
| Flink will set the execution mode to BATCH if all sources are bounded, or STREAMING if there |
| is at least one source which is unbounded. |
| |
| .. currentmodule:: pyflink.datastream.execution_mode |
| |
| .. autosummary:: |
| :toctree: api/ |
| |
| RuntimeExecutionMode.STREAMING |
| RuntimeExecutionMode.BATCH |
| RuntimeExecutionMode.AUTOMATIC |
| |
| |
| SlotSharingGroup |
| ---------------- |
| |
| .. currentmodule:: pyflink.datastream.slot_sharing_group |
| |
| .. autosummary:: |
| :toctree: api/ |
| |
| SlotSharingGroup |
| MemorySize |
