org.apache.flink.python.PythonOptions Maven / Gradle / Ivy
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* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.apache.flink.python;
import org.apache.flink.annotation.Experimental;
import org.apache.flink.annotation.PublicEvolving;
import org.apache.flink.configuration.ConfigOption;
import org.apache.flink.configuration.ConfigOptions;
import org.apache.flink.configuration.TaskManagerOptions;
import org.apache.flink.configuration.description.Description;
/** Configuration options for the Python API. */
@PublicEvolving
public class PythonOptions {
/** The maximum number of elements to include in a bundle. */
public static final ConfigOption MAX_BUNDLE_SIZE =
ConfigOptions.key("python.fn-execution.bundle.size")
.defaultValue(100000)
.withDescription(
"The maximum number of elements to include in a bundle for Python "
+ "user-defined function execution. The elements are processed asynchronously. "
+ "One bundle of elements are processed before processing the next bundle of elements. "
+ "A larger value can improve the throughput, but at the cost of more memory usage and higher latency.");
/** The maximum time to wait before finalising a bundle (in milliseconds). */
public static final ConfigOption MAX_BUNDLE_TIME_MILLS =
ConfigOptions.key("python.fn-execution.bundle.time")
.defaultValue(1000L)
.withDescription(
"Sets the waiting timeout(in milliseconds) before processing a bundle for "
+ "Python user-defined function execution. The timeout defines how long the elements of a bundle will be "
+ "buffered before being processed. Lower timeouts lead to lower tail latencies, but may affect throughput.");
/** The maximum number of elements to include in an arrow batch. */
public static final ConfigOption MAX_ARROW_BATCH_SIZE =
ConfigOptions.key("python.fn-execution.arrow.batch.size")
.defaultValue(10000)
.withDescription(
"The maximum number of elements to include in an arrow batch for Python "
+ "user-defined function execution. The arrow batch size should not exceed the "
+ "bundle size. Otherwise, the bundle size will be used as the arrow batch size.");
/** The configuration to enable or disable metric for Python execution. */
public static final ConfigOption PYTHON_METRIC_ENABLED =
ConfigOptions.key("python.metric.enabled")
.defaultValue(true)
.withDescription(
"When it is false, metric for Python will be disabled. You can "
+ "disable the metric to achieve better performance at some circumstance.");
/** The configuration to enable or disable profile for Python execution. */
public static final ConfigOption PYTHON_PROFILE_ENABLED =
ConfigOptions.key("python.profile.enabled")
.booleanType()
.defaultValue(false)
.withDescription(
"Specifies whether to enable Python worker profiling. The profile result "
+ "will be displayed in the log file of the TaskManager periodically. "
+ "The interval between each profiling is determined by the config options "
+ "python.fn-execution.bundle.size and python.fn-execution.bundle.time.");
/** The configuration to enable or disable python operator chaining. */
public static final ConfigOption PYTHON_OPERATOR_CHAINING_ENABLED =
ConfigOptions.key("python.operator-chaining.enabled")
.booleanType()
.defaultValue(true)
.withDescription(
"Python operator chaining allows non-shuffle operations to be co-located in the "
+ "same thread fully avoiding serialization and de-serialization.");
public static final ConfigOption PYTHON_FILES =
ConfigOptions.key("python.files")
.stringType()
.noDefaultValue()
.withDescription(
"Attach custom files for job. The standard resource file suffixes such as .py/.egg/.zip/.whl or "
+ "directory are all supported. These files will be added to the PYTHONPATH of both the local "
+ "client and the remote python UDF worker. Files suffixed with .zip will be extracted and added to PYTHONPATH. "
+ "Comma (',') could be used as the separator to specify multiple files. The option is equivalent to the command line option \"-pyfs\". ");
public static final ConfigOption PYTHON_REQUIREMENTS =
ConfigOptions.key("python.requirements")
.stringType()
.noDefaultValue()
.withDescription(
"Specify a requirements.txt file which defines the third-party "
+ "dependencies. These dependencies will be installed and added to the PYTHONPATH of "
+ "the python UDF worker. A directory which contains the installation packages of "
+ "these dependencies could be specified optionally. Use '#' as the separator if the "
+ "optional parameter exists. The option is equivalent to the command line option "
+ "\"-pyreq\".");
public static final ConfigOption PYTHON_ARCHIVES =
ConfigOptions.key("python.archives")
.stringType()
.noDefaultValue()
.withDescription(
"Add python archive files for job. The archive files will be extracted "
+ "to the working directory of python UDF worker. "
+ "For each archive file, a target directory is specified. If the target "
+ "directory name is specified, the archive file will be extracted to a "
+ "directory with the specified name. Otherwise, the archive file will be extracted to "
+ "a directory with the same name of the archive file. The files uploaded via this "
+ "option are accessible via relative path. '#' could be used as the separator of the "
+ "archive file path and the target directory name. Comma (',') could be used as the "
+ "separator to specify multiple archive files. This option can be used to upload the "
+ "virtual environment, the data files used in Python UDF. The data files could be "
+ "accessed in Python UDF, e.g.: f = open('data/data.txt', 'r'). The option is "
+ "equivalent to the command line option \"-pyarch\".");
public static final ConfigOption PYTHON_EXECUTABLE =
ConfigOptions.key("python.executable")
.stringType()
.defaultValue("python")
.withDescription(
"Specify the path of the python interpreter used to execute the python "
+ "UDF worker. The python UDF worker depends on Python 3.6+, Apache Beam "
+ "(version == 2.27.0), Pip (version >= 7.1.0) and SetupTools (version >= 37.0.0). "
+ "Please ensure that the specified environment meets the above requirements. The "
+ "option is equivalent to the command line option \"-pyexec\".");
public static final ConfigOption PYTHON_CLIENT_EXECUTABLE =
ConfigOptions.key("python.client.executable")
.stringType()
.defaultValue("python")
.withDescription(
Description.builder()
.text(
"The path of the Python interpreter used to launch the Python process when submitting the "
+ "Python jobs via \"flink run\" or compiling the Java/Scala jobs containing Python UDFs. "
+ "Equivalent to the command line option \"-pyclientexec\" or the environment variable PYFLINK_CLIENT_EXECUTABLE. "
+ "The priority is as following: ")
.linebreak()
.text(
"1. the configuration 'python.client.executable' defined in the source code(Only used in Flink Java SQL/Table API job call Python UDF);")
.linebreak()
.text("2. the command line option \"-pyclientexec\";")
.linebreak()
.text(
"3. the configuration 'python.client.executable' defined in flink-conf.yaml")
.linebreak()
.text("4. the environment variable PYFLINK_CLIENT_EXECUTABLE;")
.build());
/** Whether the memory used by the Python framework is managed memory. */
public static final ConfigOption USE_MANAGED_MEMORY =
ConfigOptions.key("python.fn-execution.memory.managed")
.defaultValue(true)
.withDescription(
String.format(
"If set, the Python worker will configure itself to use the "
+ "managed memory budget of the task slot. Otherwise, it will use the Off-Heap Memory "
+ "of the task slot. In this case, users should set the Task Off-Heap Memory using the "
+ "configuration key %s.",
TaskManagerOptions.TASK_OFF_HEAP_MEMORY.key()));
/** The maximum number of states cached in a Python UDF worker. */
@Experimental
public static final ConfigOption STATE_CACHE_SIZE =
ConfigOptions.key("python.state.cache-size")
.defaultValue(1000)
.withDescription(
"The maximum number of states cached in a Python UDF worker. Note that this "
+ "is an experimental flag and might not be available in future releases.");
/** The maximum number of cached items which read from Java side in a Python MapState. */
@Experimental
public static final ConfigOption MAP_STATE_READ_CACHE_SIZE =
ConfigOptions.key("python.map-state.read-cache-size")
.defaultValue(1000)
.withDescription(
"The maximum number of cached entries for a single Python MapState. "
+ "Note that this is an experimental flag and might not be available in future releases.");
/** The maximum number of write requests cached in a Python MapState. */
@Experimental
public static final ConfigOption MAP_STATE_WRITE_CACHE_SIZE =
ConfigOptions.key("python.map-state.write-cache-size")
.defaultValue(1000)
.withDescription(
"The maximum number of cached write requests for a single Python "
+ "MapState. The write requests will be flushed to the state backend (managed in "
+ "the Java operator) when the number of cached write requests exceed this limit. "
+ "Note that this is an experimental flag and might not be available in future "
+ "releases.");
/**
* The maximum number of entries sent to Python UDF worker per request when iterating a Python
* MapState.
*/
@Experimental
public static final ConfigOption MAP_STATE_ITERATE_RESPONSE_BATCH_SIZE =
ConfigOptions.key("python.map-state.iterate-response-batch-size")
.defaultValue(1000)
.withDescription(
"The maximum number of the MapState keys/entries sent to Python UDF worker "
+ "in each batch when iterating a Python MapState. Note that this is an experimental flag "
+ "and might not be available "
+ "in future releases.");
}
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