不兼容的应用程序(不兼容的应用程序怎么安装)

前沿拓展：

不兼容的应用程序

以电脑为例，不兼容的应用程序解决的方法：
　　
　　1、第一，拿任意软件做例子，右键进入其软件的属性。
　　
　　2、将弹出的属性窗口切换至兼容性面板。
　　
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用户反馈自己写的spark程序放到YANR执行偶尔报错，错误提示java.lang.IllegalArgumentException: Illegal pattern component: XXX。从日志来看是创建FastDateFormat对象报错，并且偶尔报错，难道和执行的数据有关，用户反馈相同数据也是有时成功有时失败；报错都发生在集群固定节点吗，这个也不明确，先仔细看看错误日志再说。

使用vim查看spark日志，也可使用yarn logs -applicationId $appId查看日志

23/02/08 10:15:06 ERROR Executor: Exception in task 5.3 in stage 0.0 (TID 4)
java.lang.IllegalArgumentException: Illegal pattern component: XXX
at org.apache.commons.lang3.time.FastDatePrinter.parsePattern(FastDatePrinter.java:282)
at org.apache.commons.lang3.time.FastDatePrinter.init(FastDatePrinter.java:149)
at org.apache.commons.lang3.time.FastDatePrinter.<init>(FastDatePrinter.java:142)
at org.apache.commons.lang3.time.FastDateFormat.<init>(FastDateFormat.java:384)
at org.apache.commons.lang3.time.FastDateFormat.<init>(FastDateFormat.java:369)
at org.apache.commons.lang3.time.FastDateFormat$1.createInstance(FastDateFormat.java:91)
at org.apache.commons.lang3.time.FastDateFormat$1.createInstance(FastDateFormat.java:88)
at org.apache.commons.lang3.time.FormatCache.getInstance(FormatCache.java:82)
at org.apache.commons.lang3.time.FastDateFormat.getInstance(FastDateFormat.java:165)
at org.apache.spark.sql.catalyst.json.JSONOptions.<init>(JSONOptions.scala:83)
at org.apache.spark.sql.catalyst.json.JSONOptions.<init>(JSONOptions.scala:43)
at org.apache.spark.sql.Dataset$anonfun$toJSON$1.apply(Dataset.scala:3146)
at org.apache.spark.sql.Dataset$anonfun$toJSON$1.apply(Dataset.scala:3142)
at org.apache.spark.sql.execution.MapPartitionsExec$anonfun$5.apply(objects.scala:188)
at org.apache.spark.sql.execution.MapPartitionsExec$anonfun$5.apply(objects.scala:185)
at org.apache.spark.rdd.RDD$anonfun$mapPartitionsInternal$1$anonfun$apply$25.apply(RDD.scala:836)
at org.apache.spark.rdd.RDD$anonfun$mapPartitionsInternal$1$anonfun$apply$25.apply(RDD.scala:836)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.rdd.MapPartitionsRDD.compute(MapPartitionsRDD.scala:49)
at org.apache.spark.rdd.RDD.computeOrReadCheckpoint(RDD.scala:324)
at org.apache.spark.rdd.RDD.iterator(RDD.scala:288)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:96)
at org.apache.spark.scheduler.ShuffleMapTask.runTask(ShuffleMapTask.scala:53)
at org.apache.spark.scheduler.Task.run(Task.scala:109)
at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:345)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1142)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:617)
at java.lang.Thread.run(Thread.java:748)

根据日志错误是从spark catalyst出来的，即org.apache.spark.sql.catalyst.json.JSONOptions类的83行，创建FastDateFormat实例的过程发生异常。查看spark JSONOptions类源码，我们发现报错行入参处恰好有字符XXX，是否和这儿有关继续看创建创建FastDateFormat过程，跟踪源码到commons-lang3的org.apache.commons.lang3.time.FastDatePrinter类

//Spark源码
val timestampFormat: FastDateFormat =
FastDateFormat.getInstance(
parameters.getOrElse("timestampFormat", "yyyy-MM-dd'T'HH:mm:ss.SSSXXX"), timeZone, Locale.US)

找到spark源码引用的commons-lang3-3.8.1.jar包，进入在FastDatePrinter类搜索关键词Illegal pattern component，关键词Illegal pattern component找到了，仅此一处，但仔细一看行号对不上，说明spark加载的FastDateFormat并不是3.8.1版本，那从哪儿来的呢

protected List<Rule> parsePattern() {
//。。。省略
case 'M': // month in year (text and number)
if (tokenLen >= 4) {
rule = new TextField(Calendar.MONTH, months);
} else if (tokenLen == 3) {
rule = new TextField(Calendar.MONTH, shortMonths);
} else if (tokenLen == 2) {
rule = TwoDigitMonthField.INSTANCE;
} else {
rule = UnpaddedMonthField.INSTANCE;
}
break;
case 'd': // day in month (number)
rule = selectNumberRule(Calendar.DAY_OF_MONTH, tokenLen);
break;
//。。。省略
default:
throw new IllegalArgumentException("Illegal pattern component: " + token);
}

rules.add(rule);
}

return rules;
}

第一看用户代码是否引入了commons-lang3，解压fat-jar后确实存在org.apache.commons.lang3.time.FastDateFormat，但版本也是3.8.1，不会这儿引起的。查找spark安装目录，执行命令find . -name "commons-lang3*"进行查找，只有一个commons-lang3-3.8.1.jar在${SPARK_HOME}/jars/目录下，再查找hadoop目录，发现了有commons-lang3，但下载下来反编译后，检查行号仍然对不上，说明也不是加载的这个jar，奇怪为啥没找到哪儿来的类，想尝试用arthas查看但是不确定executor会启动在哪个节点，且没多久就报错结束了。

尝试添加JVM参数打印spark driver/executor加载的类，从日志看spark driver加载了正确的包commons-lang3-3.8.1.jar，spark executor没找到想要日志，可能verbose输出的时候还没用到FastDateFormat类？下面是spark-submit添加JVM参数的方式：

spark-submit \
–master yarn \
–driver-memory 4G \
–name 'AppName' \
–conf 'spark.driver.extraJavaOptions=-verbose:class' \
–conf 'spark.executor.extraJavaOptions=-verbose:class' \

用户催的急没时间了，改代码看看FastDateFormat哪儿来的，顺便在发生异常的情况下重新创建FastDateFormat对象，去掉参数XXX，这样避免因为不支持XXX参数而导致程序失败退出。

// 修改org.apache.spark.sql.catalyst.json.JSONOptions源码，捕获timestampFormat实例化的异常
// 捕获异常，打印Message和类加载来源
logWarning("==============>>>" + e.getMessage)
val clazz = FastDateFormat.getInstance().getClass
val location = clazz.getResource('/' + clazz.getName.replace('.', '/') + ".class")
logWarning("resource location: " + location.toString)

打包编译并替换spark对应jar包，运行成功了且捕获到了异常信息，发现FastDateFormat来源hive-exec-1.2.1.spark2.jar，才想起忘了搜索jar包里的class类，除了包名commons-lang3*，还需要查找jar里的内容，hive-exec刚好是个fat-jar

23/02/08 17:12:39 WARN JSONOptions: ==============>>>Illegal pattern component: XXX
23/02/08 17:12:39 WARN JSONOptions: resource location: jar:file:/data/hadoop/yarn/local/usercache/…/__spark_libs__1238265929018908261.zip/hive-exec-1.2.1.spark2.jar!/org/apache/commons/lang3/time/FastDateFormat.class

spark的commons-lang3-3.8.1.jar和hive-exec-1.2.1.spark2.jar都在目录${SPARK_HOME}/jar/下，百度了下这种情况下类加载顺序和CLASSPATH填写的JAR顺序以及创建时间都相关（没找到一个权威的文章），期间尝试过设置spark-submit参数：–conf 'spark.executor.extraClassPath=commons-lang3-3.8.1.jar'来优先加载这个jar，仍然执行报错，后来看日志的时候偶然发现 CLASSPATH的路径时错误的，如下日志，看来spark.executor.extraClassPath的作用就是把jar包放到classpath的最前面，这样达到优先加载的目的。

export SPARK_YARN_STAGING_DIR="hdfs://nnHA/user/p55_u34_tsp_caihong/.sparkStaging/application_1670726876109_157924"
export CLASSPATH="commons-lang3-3.8.1.jar:$PWD:$PWD/__spark_conf__:$PWD/__spark_libs__/*:/etc/hadoop/conf:/usr/lib/hadoop/lib/*:/usr/lib/hadoop/.//*:/usr/lib/hadoop-hdfs/./:/usr/lib/hadoop-hdfs/lib/*:/usr/lib/hadoop-hdfs/.//*:/usr/lib/hadoop-yarn/lib/*:/usr/lib/hadoop-yarn/.//*:/usr/lib/hadoop-mapreduce/lib/*:/usr/lib/hadoop-mapreduce/.//*:/etc/hadoop/conf:/usr/lib/hadoop/libs/*:/usr/lib/hadoop/.//*:/usr/lib/hadoop-hdfs/./:/usr/lib/hadoop-hdfs/lib/*:/usr/lib/hadoop-hdfs/.//*:/usr/lib/hadoop-yarn/lib/*:/usr/lib/hadoop-yarn/.//*:/usr/lib/hadoop-mapreduce/lib/*:/usr/lib/hadoop-mapreduce/.//*:$PWD/__spark_conf__/__hadoop_conf__"

spark.executor.extraClassPath必须使用全路径，尝试修改spark-submit命令，写全spark.executor.extraClassPath路径，重新执行问题解决，没在报错。但是仍有疑问：为啥偶尔成功失败，按理说两个jar包虽然都在jars目录，也会有固定的加载顺序吧，不解。。。了解的同学还请在评论区告之，不胜感激。修改源码和设置spark.executor.extraClassPath参数都能有效解决这个问题。

spark-submit \
–master yarn \
–driver-memory 4G \
–name 'AppName' \
–conf 'spark.driver.extraJavaOptions=-verbose:class' \
–conf 'spark.executor.extraJavaOptions=-verbose:class' \
–conf 'spark.executor.extraClassPath=${SPARK_HOME}/jars/commons-lang3-3.8.1.jar' \