命令行方法(感谢Homebrew团队以及@vladimir-kempik和其他openjdk JEP-391分支贡献者的辛勤工作)

# Install Homebrew
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Install OpenJDK
brew install openjdk

确认安装成功:

$(brew --prefix openjdk)/bin/java --version

验证它是arm64硬件:

file $(brew --prefix openjdk)/bin/java     
# /opt/homebrew/opt/openjdk/bin/java: Mach-O 64-bit executable arm64

注意:要在系统范围内安装openjdk，请遵循Homebrew提供的屏幕说明。

我尝试过Azul JDK 8。

我只是想说，虽然Azul JDK在Apple M1上原生运行，而且速度非常快，但仍然存在一些问题。特别是当一些Java代码需要调用c++代码时。

例如，我是一名大数据开发人员。我开始使用Azul JDK进行开发工作流程。但是我注意到切换后某些测试开始失败。例如，当测试写入Parquet/Avro文件时，它会失败。我认为这是因为有一些用c++为Parquet/Avro编写的原生东西，而不是为M1编译的。

由于这个特殊的原因，我被迫使用速度较慢的非m1 JDK。没有什么问题。

这里有一个我用Azul得到的错误的例子，我没有得到非m1 jdk:

- convert Base64 JSON back to rpo Avro *** FAILED ***
  org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 10.0 failed 1 times, most recent failure: Lost task 0.0 in stage 10.0 (TID 14, localhost, executor driver): org.xerial.snappy.SnappyError: [FAILED_TO_LOAD_NATIVE_LIBRARY] no native library is found for os.name=Mac and os.arch=aarch64
        at org.xerial.snappy.SnappyLoader.findNativeLibrary(SnappyLoader.java:331)
        at org.xerial.snappy.SnappyLoader.loadNativeLibrary(SnappyLoader.java:171)
        at org.xerial.snappy.SnappyLoader.load(SnappyLoader.java:152)
        at org.xerial.snappy.Snappy.<clinit>(Snappy.java:47)
        at org.apache.avro.file.SnappyCodec.compress(SnappyCodec.java:43)
        at org.apache.avro.file.DataFileStream$DataBlock.compressUsing(DataFileStream.java:358)
        at org.apache.avro.file.DataFileWriter.writeBlock(DataFileWriter.java:382)
        at org.apache.avro.file.DataFileWriter.sync(DataFileWriter.java:401)
        at org.apache.avro.file.DataFileWriter.flush(DataFileWriter.java:410)
        at org.apache.avro.file.DataFileWriter.close(DataFileWriter.java:433)
        at org.apache.avro.mapred.AvroOutputFormat$1.close(AvroOutputFormat.java:170)
        at org.apache.spark.internal.io.SparkHadoopWriter.close(SparkHadoopWriter.scala:101)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$12$$anonfun$apply$5.apply$mcV$sp(PairRDDFunctions.scala:1145)
        at org.apache.spark.util.Utils$.tryWithSafeFinallyAndFailureCallbacks(Utils.scala:1393)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1145)
        at org.apache.spark.rdd.PairRDDFunctions$$anonfun$saveAsHadoopDataset$1$$anonfun$12.apply(PairRDDFunctions.scala:1125)
        at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:87)
        at org.apache.spark.scheduler.Task.run(Task.scala:108)
        at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:335)
        at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
        at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
        at java.lang.Thread.run(Thread.java:748)

Driver stacktrace:
  at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1499)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1487)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1486)
  at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
  at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
  at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1486)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
  at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:814)
  at scala.Option.foreach(Option.scala:257)
  at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:814)
  ...
  Cause: org.xerial.snappy.SnappyError: [FAILED_TO_LOAD_NATIVE_LIBRARY] no native library is found for os.name=Mac and os.arch=aarch64
  at org.xerial.snappy.SnappyLoader.findNativeLibrary(SnappyLoader.java:331)
  at org.xerial.snappy.SnappyLoader.loadNativeLibrary(SnappyLoader.java:171)
  at org.xerial.snappy.SnappyLoader.load(SnappyLoader.java:152)
  at org.xerial.snappy.Snappy.<clinit>(Snappy.java:47)
  at org.apache.avro.file.SnappyCodec.compress(SnappyCodec.java:43)
  at org.apache.avro.file.DataFileStream$DataBlock.compressUsing(DataFileStream.java:358)
  at org.apache.avro.file.DataFileWriter.writeBlock(DataFileWriter.java:382)
  at org.apache.avro.file.DataFileWriter.sync(DataFileWriter.java:401)
  at org.apache.avro.file.DataFileWriter.flush(DataFileWriter.java:410)
  at org.apache.avro.file.DataFileWriter.close(DataFileWriter.java:433)

正如你所看到的，它说:Cause: org.xerial.snappy.SnappyError: [FAILED_TO_LOAD_NATIVE_LIBRARY] no native library is found for os.name=Mac and os.arch=aarch64

我谷歌了一下这个问题，他们说原生库是为Spark的后续版本编译的，不幸的是。

这让我非常沮丧，我现在想要一台Windows笔记本电脑，哈哈。在M1芯片上运行Intel JDK有时会很慢，我不希望这样。

小心!

Update: They released new versions of their libraries with support for M1, I updated them in the projects and everything works, thank God. Sometimes these "native code errors" manifest themselves with different exceptions and this is additional P.I.T.A. that I have to deal with while my colleagues on windows laptops don't need to deal with it. The errors can be a bit unclear sometimes, but if you see something about native code in the error log, or words like "jna" or "jni", then it's an M1 chip problem.

我成功地使用Azul OpenJDK和NetBeans在新的Apple M1芯片上开发Java应用程序。

配置:

zulu16.0.65-ea-jdk16.0.0-ea.24-macos_aarch64 NetBeans 12.1和Maven。

命令行方法(感谢Homebrew团队以及@vladimir-kempik和其他openjdk JEP-391分支贡献者的辛勤工作)

# Install Homebrew
/bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)"

# Install OpenJDK
brew install openjdk

确认安装成功:

$(brew --prefix openjdk)/bin/java --version

验证它是arm64硬件:

file $(brew --prefix openjdk)/bin/java     
# /opt/homebrew/opt/openjdk/bin/java: Mach-O 64-bit executable arm64

注意:要在系统范围内安装openjdk，请遵循Homebrew提供的屏幕说明。

Azul在其网站的下载部分提供macOS ARM版本的OpenJDK。虽然我还没有尝试过，但Azul一直是JDK的长期开发人员。

一旦你解包了Azul JDK，你必须在它里面翻找，直到你找到zulu-11。jdk目录(假设您已经下载了jdk 11)，然后将其复制到/Library/Java/JavaVirtualMachines。

您可以从以下网站下载Liberica JDK:

https://bell-sw.com/pages/downloads/?os=macOS&architecture=ARM

在IntelliJ IDEA for M1中，JetBrains运行时也是原生的(ARM64)。