打印日志信息

客户端日志

from pyflink.table import EnvironmentSettings, TableEnvironment
# 创建 TableEnvironment
env_settings = EnvironmentSettings.in_streaming_mode()
table_env = TableEnvironment.create(env_settings)
table = table_env.from_elements([(1, 'Hi'), (2, 'Hello')])
# 使用 logging 模块
import logging
logging.warning(table.get_schema())
logging.warning(table.to_pandas())
# 使用 print 函数
print(table.get_schema())
print(table.to_pandas())

注意: 客户端缺省的日志级别是 WARNING，因此，只有日志级别在 WARNING 及以上的日志信息才会打印在客户端的日志文件中。

查看客户端日志

$ python -c "import pyflink;import os;print(os.path.dirname(os.path.abspath(pyflink.__file__))+'/log')"

服务器端日志

@udf(result_type=DataTypes.BIGINT())
def add(i, j):
    # 使用 logging 模块
    import logging
    logging.info("debug")
    # 使用 print 函数
    print('debug')
    return i + j

注意: 服务器端缺省的日志级别是 INFO，因此，只有日志级别在 INFO 及以上的日志信息才会打印在 TaskManager 的日志文件中。

查看服务器日志

  <property>
    <name>yarn.nodemanager.log-dirs</name>
    <value>/data/hadoop/yarn/log</value>
  </property>

调试 Python UDF

本地调试

远程调试

1. 在 PyCharm 里创建一个 Python Remote Debugrun -> Python Remote Debug -> + -> 选择一个 port (e.g. 6789)
2. 安装 pydevd-pycharm 工具

$ pip install pydevd-pycharm

1. 在你的 Python UDF 里面添加如下的代码

import pydevd_pycharm
pydevd_pycharm.settrace('localhost', port=6789, stdoutToServer=True, stderrToServer=True)

1. 启动刚刚创建的 Python Remote Dubug Server
2. 运行你的 Python 代码

可以参考 PyCharm 官网教程

https://www.jetbrains.com/help/pycharm/remote-debugging-with-product.html

Profiling Python UDF

t_env.get_config().get_configuration().set_boolean("python.profile.enabled", True)

PyFlink 应用调试实战

这里主要介绍如何打印日志信息以及打开 profile 来分析 Python UDF 性能，调试 Python UDF 与调试普通 Python 函数调试过程一样，这里就不在赘述，远程调试可以参考 PyCharm 官网教程。

完成示例程序如下：

import argparse
import logging
import sys
from pyflink.common import Row
from pyflink.table import (EnvironmentSettings, TableEnvironment, TableDescriptor, Schema,
                           DataTypes, FormatDescriptor)
from pyflink.table.expressions import lit, col
from pyflink.table.udf import udtf
word_count_data = ["To be, or not to be,--that is the question:--",
                   "Whether 'tis nobler in the mind to suffer",
                   "The slings and arrows of outrageous fortune",
                   "Or to take arms against a sea of troubles,",
                   "And by opposing end them?--To die,--to sleep,--",
                   "No more; and by a sleep to say we end",
                   "The heartache, and the thousand natural shocks",
                   "That flesh is heir to,--'tis a consummation",
                   "Devoutly to be wish'd. To die,--to sleep;--",
                   "To sleep! perchance to dream:--ay, there's the rub;",
                   "For in that sleep of death what dreams may come,",
                   "When we have shuffled off this mortal coil,",
                   "Must give us pause: there's the respect",
                   "That makes calamity of so long life;",
                   "For who would bear the whips and scorns of time,",
                   "The oppressor's wrong, the proud man's contumely,",
                   "The pangs of despis'd love, the law's delay,",
                   "The insolence of office, and the spurns",
                   "That patient merit of the unworthy takes,",
                   "When he himself might his quietus make",
                   "With a bare bodkin? who would these fardels bear,",
                   "To grunt and sweat under a weary life,",
                   "But that the dread of something after death,--",
                   "The undiscover'd country, from whose bourn",
                   "No traveller returns,--puzzles the will,",
                   "And makes us rather bear those ills we have",
                   "Than fly to others that we know not of?",
                   "Thus conscience does make cowards of us all;",
                   "And thus the native hue of resolution",
                   "Is sicklied o'er with the pale cast of thought;",
                   "And enterprises of great pith and moment,",
                   "With this regard, their currents turn awry,",
                   "And lose the name of action.--Soft you now!",
                   "The fair Ophelia!--Nymph, in thy orisons",
                   "Be all my sins remember'd."]
def word_count(input_path, output_path):
    t_env = TableEnvironment.create(EnvironmentSettings.in_streaming_mode())
    # write all the data to one file
    t_env.get_config().get_configuration().set_string("parallelism.default", "1")
    # open profile
    t_env.get_config().get_configuration().set_boolean("python.profile.enabled", True)
    # define the source
    if input_path is not None:
        t_env.create_temporary_table(
            'source',
            TableDescriptor.for_connector('filesystem')
                           .schema(Schema.new_builder()
                                   .column('word', DataTypes.STRING())
                                   .build())
                           .option('path', input_path)
                           .format('csv')
                           .build())
        tab = t_env.from_path('source')
    else:
        print("Executing word_count example with default input data set.")
        print("Use --input to specify file input.")
        tab = t_env.from_elements(map(lambda i: (i,), word_count_data),
                                  DataTypes.ROW([DataTypes.FIELD('line', DataTypes.STRING())]))
    # define the sink
    if output_path is not None:
        t_env.create_temporary_table(
            'sink',
            TableDescriptor.for_connector('filesystem')
                           .schema(Schema.new_builder()
                                   .column('word', DataTypes.STRING())
                                   .column('count', DataTypes.BIGINT())
                                   .build())
                           .option('path', output_path)
                           .format(FormatDescriptor.for_format('canal-json')
                                   .build())
                           .build())
    else:
        print("Printing result to stdout. Use --output to specify output path.")
        t_env.create_temporary_table(
            'sink',
            TableDescriptor.for_connector('print')
                           .schema(Schema.new_builder()
                                   .column('word', DataTypes.STRING())
                                   .column('count', DataTypes.BIGINT())
                                   .build())
                           .build())
    @udtf(result_types=[DataTypes.STRING()])
    def split(line: Row):
        print("==========split===========")
        print(line[0])
        for s in line[0].split():
            yield Row(s)
    # compute word count
    tab.flat_map(split).alias('word') \
       .group_by(col('word')) \
       .select(col('word'), lit(1).count) \
       .execute_insert('sink') \
       .wait()
    # remove .wait if submitting to a remote cluster, refer to
    # https://nightlies.apache.org/flink/flink-docs-stable/docs/dev/python/faq/#wait-for-jobs-to-finish-when-executing-jobs-in-mini-cluster
    # for more details
if __name__ == '__main__':
    logging.basicConfig(stream=sys.stdout, level=logging.INFO, format="%(message)s")
    parser = argparse.ArgumentParser()
    parser.add_argument(
        '--input',
        dest='input',
        required=False,
        help='Input file to process.')
    parser.add_argument(
        '--output',
        dest='output',
        required=False,
        help='Output file to write results to.')
    argv = sys.argv[1:]
    known_args, _ = parser.parse_known_args(argv)
    word_count(known_args.input, known_args.output)

• 启动 Flink Session 集群

$FLINK_HOME/bin/yarn-session.sh --detached

• 提交 Job

$FLINK_HOME/bin/flink run --python word_count.py

ln -s /usr/bin/python3 /usr/bin/python

 $FLINK_HOME/bin/flink run  -pyclientexec python3 -pyexec python3  --python word_count.py

• 查看控制台输出

• 查看客户端日志

• 查看服务器输出

• 查看服务器日志

• 查看 profile 日志