这里有几个坑要踩：

1. pip 的源，这里要设置下，否则好慢 https://blog.csdn.net/furzoom/article/details/53897318
2. 如果你使用的是 java9，降级到 java8 吧
3. 如果你用 pycharm，那么还得再配置个 java8 的 JAVA_HOME

所以总的来说，如果你在 mac 上的下载了，spark 2.3，然后你也用 pycharm 的话，那么：

1. 先创建个项目
2. 在这个项目的 project interpreter 里找到 pip，给他换个源：https://pypi.tuna.tsinghua.edu.cn/simple/
3. 然后安装 pyspark
4. 然后再安装 java8，装好之后，给 pycharm 加环境变量，只要加个 JAVA_HOME 指向 java8 就可以了。
5. 然后就可以用了。

否则你会遇到下面的异常：

/Users/lihuazhang/code/spark-learn/one/venv/bin/python /Users/lihuazhang/code/spark-learn/one/SimpleApp.py
WARNING: An illegal reflective access operation has occurred
WARNING: Illegal reflective access by org.apache.hadoop.security.authentication.util.KerberosUtil (file:/Users/lihuazhang/code/spark-learn/one/venv/lib/python2.7/site-packages/pyspark/jars/hadoop-auth-2.7.3.jar) to method sun.security.krb5.Config.getInstance()
WARNING: Please consider reporting this to the maintainers of org.apache.hadoop.security.authentication.util.KerberosUtil
WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations
WARNING: All illegal access operations will be denied in a future release
2018-03-25 00:44:51 WARN  NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Setting default log level to "WARN".
To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).
2018-03-25 00:44:51 WARN  Utils:66 - Service 'SparkUI' could not bind on port 4040. Attempting port 4041.
Traceback (most recent call last):
  File "/Users/lihuazhang/code/spark-learn/one/SimpleApp.py", line 9, in <module>
    numAs = logData.filter(logData.value.contains('a')).count()
  File "/Users/lihuazhang/code/spark-learn/one/venv/lib/python2.7/site-packages/pyspark/sql/dataframe.py", line 455, in count
    return int(self._jdf.count())
  File "/Users/lihuazhang/code/spark-learn/one/venv/lib/python2.7/site-packages/py4j/java_gateway.py", line 1160, in __call__
    answer, self.gateway_client, self.target_id, self.name)
  File "/Users/lihuazhang/code/spark-learn/one/venv/lib/python2.7/site-packages/pyspark/sql/utils.py", line 63, in deco
    return f(*a, **kw)
  File "/Users/lihuazhang/code/spark-learn/one/venv/lib/python2.7/site-packages/py4j/protocol.py", line 320, in get_return_value
    format(target_id, ".", name), value)
py4j.protocol.Py4JJavaError: An error occurred while calling o35.count.
: java.lang.IllegalArgumentException
    at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.<init>(Unknown Source)
    at org.apache.spark.util.ClosureCleaner$.getClassReader(ClosureCleaner.scala:46)
    at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:449)
    at org.apache.spark.util.FieldAccessFinder$$anon$3$$anonfun$visitMethodInsn$2.apply(ClosureCleaner.scala:432)
    at scala.collection.TraversableLike$WithFilter$$anonfun$foreach$1.apply(TraversableLike.scala:733)
    at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
    at scala.collection.mutable.HashMap$$anon$1$$anonfun$foreach$2.apply(HashMap.scala:103)
    at scala.collection.mutable.HashTable$class.foreachEntry(HashTable.scala:230)
    at scala.collection.mutable.HashMap.foreachEntry(HashMap.scala:40)
    at scala.collection.mutable.HashMap$$anon$1.foreach(HashMap.scala:103)
    at scala.collection.TraversableLike$WithFilter.foreach(TraversableLike.scala:732)
    at org.apache.spark.util.FieldAccessFinder$$anon$3.visitMethodInsn(ClosureCleaner.scala:432)
    at org.apache.xbean.asm5.ClassReader.a(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.b(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
    at org.apache.xbean.asm5.ClassReader.accept(Unknown Source)
    at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:262)
    at org.apache.spark.util.ClosureCleaner$$anonfun$org$apache$spark$util$ClosureCleaner$$clean$14.apply(ClosureCleaner.scala:261)
    at scala.collection.immutable.List.foreach(List.scala:381)
    at org.apache.spark.util.ClosureCleaner$.org$apache$spark$util$ClosureCleaner$$clean(ClosureCleaner.scala:261)
    at org.apache.spark.util.ClosureCleaner$.clean(ClosureCleaner.scala:159)
    at org.apache.spark.SparkContext.clean(SparkContext.scala:2292)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2066)
    at org.apache.spark.SparkContext.runJob(SparkContext.scala:2092)
    at org.apache.spark.rdd.RDD$$anonfun$collect$1.apply(RDD.scala:939)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:151)
    at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:112)
    at org.apache.spark.rdd.RDD.withScope(RDD.scala:363)
    at org.apache.spark.rdd.RDD.collect(RDD.scala:938)
    at org.apache.spark.sql.execution.SparkPlan.executeCollect(SparkPlan.scala:297)
    at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2770)
    at org.apache.spark.sql.Dataset$$anonfun$count$1.apply(Dataset.scala:2769)
    at org.apache.spark.sql.Dataset$$anonfun$52.apply(Dataset.scala:3253)
    at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:77)
    at org.apache.spark.sql.Dataset.withAction(Dataset.scala:3252)
    at org.apache.spark.sql.Dataset.count(Dataset.scala:2769)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
    at java.base/jdk.internal.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62)
    at java.base/jdk.internal.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
    at java.base/java.lang.reflect.Method.invoke(Method.java:564)
    at py4j.reflection.MethodInvoker.invoke(MethodInvoker.java:244)
    at py4j.reflection.ReflectionEngine.invoke(ReflectionEngine.java:357)
    at py4j.Gateway.invoke(Gateway.java:282)
    at py4j.commands.AbstractCommand.invokeMethod(AbstractCommand.java:132)
    at py4j.commands.CallCommand.execute(CallCommand.java:79)
    at py4j.GatewayConnection.run(GatewayConnection.java:214)
    at java.base/java.lang.Thread.run(Thread.java:844)


Process finished with exit code 1

https://stackoverflow.com/questions/34685905/how-to-link-pycharm-with-pyspark
更新下，现在的 pycharm 的配置方式有些变化。

我也会这样做 但是用例还是要设计的啊。。。

挺多的吧， @cc_fiend 就是个中好手

这个答复我比较喜欢

隔天隔周隔月不考虑下么？

这是考你思路的。。

用公司邮箱吧

猎头？

对的

jsapi 错了吧

用到你的规划里去

看主贴，补充了邮箱

可以啊，非常没问题

@qa8335351 应该修好了

不行，分类不是标签，社区目前没有标签

这个放到普通应用也可以

生气了，我明天就解决这个问题

写一写不难吧，关键是设计出对应测试用例，自证自己的实现是正确的

你这个方法是自己写的？

关于第一个，要追逐用户的话，肯定做不到真正匿名。
第二个，本地的 form storage 有的，但是如果草稿多了，本地存储也太大了。目前的草稿功能其实是 topic 状态集。

匿名你还草稿。。。够腹黑啊

面试的时候，如何描述自己的项目

首先你要给人家介绍清楚，你这个项目的产品是什么？话不要多，比如我们的产品是直播应用，市场上竞品是什么，这里说个 top 1 的，然后说下特色是什么，如果知道用户数据也可以说下。

接着，讲下项目产品有几个端，服务端，客户端，安卓，ios。简单说下，如果面试者还有兴趣，你可以把技术架构说一下，这个挺难的。得好好看看自己产品。

一般到这里，面试官会问，你在项目中干嘛了。那你就要说你在项目中承担的角色，是测试总控，还是某个模块负责人。如果是总控就要说说你的测试计划和测试策略，如果负责测试模块的，就要说说是哪些模块。这些模块的作用是什么？

最后，说说你取得的成绩。

我明白了，关键在：

SELECT DataTime,
(
    SELECT DataTime
    FROM TestTest Alias
    WHERE TestTest.DataTime > Alias.DataTime
    ORDER BY DataTime DESC
    LIMIT 1
) AS NewDate
FROM TestTest

里面

SELECT DataTime
FROM TestTest Alias
WHERE TestTest.DataTime > Alias.DataTime
ORDER BY DataTime DESC
LIMIT 1

这个子查询不能单独存在，必须和外面的一起。

你这是问如何回答的套路吧