如何禁用 PySpark 在运行时打印信息

我已经开始使用 PySpark。PySpark 的版本是3.5.4，它是通过进行安装的pip。

这是我的代码：

from pyspark.sql import SparkSession
pyspark = SparkSession.builder.master("local[8]").appName("test").getOrCreate()
df = pyspark.read.csv("test.csv", header=True)print(df.show())

每次我运行该程序时使用：

python test_01.py

它打印有关 pyspark 的所有信息（黄色）：

如何禁用它，这样它就不会打印它。

解决办法：

不同的线条来自不同的来源。
- Windows（“成功：... ”），
- spark启动器shell /批处理脚本（“ ::加载设置 ::... ”）
- 使用 log4j2 记录核心 spark 代码
- 使用核心火花代码打印System.out.println()
不同的行写入不同的fds（std-out，std-error，log4j日志文件）
Spark 针对不同目的提供了不同的“脚本”（pyspark、spark-submit、spark-shell、 ...）。您可能在这里使用了错误的脚本。

基于你想要达成的目标，最简单的方法是使用spark-submit，它适用于无界面执行：

CMD> cat test.py
from pyspark.sql import SparkSession
spark = SparkSession.builder \.config('spark.jars.packages', 'io.delta:delta-core_2.12:2.4.0') \  # just to produce logs.getOrCreate()spark.createDataFrame(data=[(i,) for i in range(5)], schema='id: int').show()CMD> spark-submit test.py
+---+
| id|
+---+
|  0|
|  1|
|  2|
|  3|
|  4|
+---+CMD>

要了解谁在向哪个 fd 写入什么是一个繁琐的过程，它甚至可能因平台（Linux/Windows/Mac）而异。我不推荐这样做。但如果你真的想要，这里有一些提示：

从您的原始代码：

print(df.show())

df.show()打印df到标准输出并返回None。
print(df.show())打印None到标准输出。

运行使用python而不是spark-submit：

CMD> python test.py
:: loading settings :: url = jar:file:/C:/My/.venv/Lib/site-packages/pyspark/jars/ivy-2.5.1.jar!/org/apache/ivy/core/settings/ivysettings.xml
Ivy Default Cache set to: C:\Users\e679994\.ivy2\cache
The jars for the packages stored in: C:\Users\e679994\.ivy2\jars
io.delta#delta-core_2.12 added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent-499a6ac1-b961-44da-af58-de97e4357cbf;1.0confs: [default]found io.delta#delta-core_2.12;2.4.0 in centralfound io.delta#delta-storage;2.4.0 in centralfound org.antlr#antlr4-runtime;4.9.3 in central
:: resolution report :: resolve 171ms :: artifacts dl 8ms:: modules in use:io.delta#delta-core_2.12;2.4.0 from central in [default]io.delta#delta-storage;2.4.0 from central in [default]org.antlr#antlr4-runtime;4.9.3 from central in [default]---------------------------------------------------------------------|                  |            modules            ||   artifacts   ||       conf       | number| search|dwnlded|evicted|| number|dwnlded|---------------------------------------------------------------------|      default     |   3   |   0   |   0   |   0   ||   3   |   0   |---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent-499a6ac1-b961-44da-af58-de97e4357cbfconfs: [default]0 artifacts copied, 3 already retrieved (0kB/7ms)
+---+
| id|
+---+
|  0|
|  1|
|  2|
|  3|
|  4|
+---+CMD> SUCCESS: The process with PID 38136 (child process of PID 38196) has been terminated.
SUCCESS: The process with PID 38196 (child process of PID 35316) has been terminated.
SUCCESS: The process with PID 35316 (child process of PID 22336) has been terminated.CMD>

重定向stdout（fd=1）到一个文件：

CMD> python test.py > out.txt 2> err.txt

CMD> 
CMD> cat out.txt
:: loading settings :: url = jar:file:/C:/My/.venv/Lib/site-packages/pyspark/jars/ivy-2.5.1.jar!/org/apache/ivy/core/settings/ivysettings.xml
+---+
| id|
+---+
|  0|
|  1|
|  2|
|  3|
|  4|
+---+SUCCESS: The process with PID 25080 (child process of PID 38032) has been terminated.
SUCCESS: The process with PID 38032 (child process of PID 21176) has been terminated.
SUCCESS: The process with PID 21176 (child process of PID 38148) has been terminated.
SUCCESS: The process with PID 38148 (child process of PID 32456) has been terminated.
SUCCESS: The process with PID 32456 (child process of PID 31656) has been terminated.CMD>

重定向stderr（fd=2）到一个文件：

CMD> cat err.txt
Ivy Default Cache set to: C:\Users\kash\.ivy2\cache
The jars for the packages stored in: C:\Users\kash\.ivy2\jars
io.delta#delta-core_2.12 added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent-597f3c82-718d-498b-b00e-7928264c307a;1.0confs: [default]found io.delta#delta-core_2.12;2.4.0 in centralfound io.delta#delta-storage;2.4.0 in centralfound org.antlr#antlr4-runtime;4.9.3 in central
:: resolution report :: resolve 111ms :: artifacts dl 5ms:: modules in use:io.delta#delta-core_2.12;2.4.0 from central in [default]io.delta#delta-storage;2.4.0 from central in [default]org.antlr#antlr4-runtime;4.9.3 from central in [default]---------------------------------------------------------------------|                  |            modules            ||   artifacts   ||       conf       | number| search|dwnlded|evicted|| number|dwnlded|---------------------------------------------------------------------|      default     |   3   |   0   |   0   |   0   ||   3   |   0   |---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent-597f3c82-718d-498b-b00e-7928264c307aconfs: [default]0 artifacts copied, 3 already retrieved (0kB/5ms)CMD>

SUCCESS: The process with PID
- 注意这是在 AFTER 之后打印的CMD>。即在完成以下执行后由“Windows”打印python
- 你不会在 Linux 上看到它。例如从我的 Linux 机器上：

kash@ub$ python test.py
19:15:50.037 [main] WARN  org.apache.spark.util.Utils - Your hostname, ub resolves to a loopback address: 127.0.1.1; using 192.168.177.129 instead (on interface ens33)
19:15:50.049 [main] WARN  org.apache.spark.util.Utils - Set SPARK_LOCAL_IP if you need to bind to another address
:: loading settings :: url = jar:file:/home/kash/workspaces/spark-log-test/.venv/lib/python3.9/site-packages/pyspark/jars/ivy-2.5.0.jar!/org/apache/ivy/core/settings/ivysettings.xml
Ivy Default Cache set to: /home/kash/.ivy2/cache
The jars for the packages stored in: /home/kash/.ivy2/jars
io.delta#delta-core_2.12 added as a dependency
:: resolving dependencies :: org.apache.spark#spark-submit-parent-7d38e7a2-a0e5-47fa-bfda-2cb5b8b443e0;1.0confs: [default]found io.delta#delta-core_2.12;2.4.0 in spark-listfound io.delta#delta-storage;2.4.0 in spark-listfound org.antlr#antlr4-runtime;4.9.3 in spark-list
:: resolution report :: resolve 390ms :: artifacts dl 10ms:: modules in use:io.delta#delta-core_2.12;2.4.0 from spark-list in [default]io.delta#delta-storage;2.4.0 from spark-list in [default]org.antlr#antlr4-runtime;4.9.3 from spark-list in [default]---------------------------------------------------------------------|                  |            modules            ||   artifacts   ||       conf       | number| search|dwnlded|evicted|| number|dwnlded|---------------------------------------------------------------------|      default     |   3   |   0   |   0   |   0   ||   3   |   0   |---------------------------------------------------------------------
:: retrieving :: org.apache.spark#spark-submit-parent-7d38e7a2-a0e5-47fa-bfda-2cb5b8b443e0confs: [default]0 artifacts copied, 3 already retrieved (0kB/19ms)
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
+---+                                                                           
| id|
+---+
|  0|
|  1|
|  2|
|  3|
|  4|
+---+kash@ub$

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