Question

在SparkSQL -(void)dismissStartupAlertView:(BOOL)buttonClicked { CGRect rect = m_customStartupView.view.frame; if(IPHONE_5) { rect.origin.y = 520 } else { rect.origin.y = 420 } m_customStartupView.view.frame = rect; [UIView beginAnimations:@"ShowView" context:nil]; [UIView setAnimationCurve:UIViewAnimationCurveEaseInOut]; [UIView setAnimationDuration:0.2]; [UIView setAnimationDelegate:self]; [UIView setAnimationDidStopSelector:@selector(animationDidStop:finished:context:)]; if(IPHONE_5) { rect.origin.y = 568; } else { rect.origin.y = 480; } m_customStartupView.view.frame = rect; [UIView commitAnimations]; } - (void)animationDidStop:(NSString *)animationID finished:(NSNumber *)finished context:(void *)context { if([animationID isEqualToString:@"ShowView"]) { [m_customStartupView willMoveToParentViewController:nil]; [m_customStartupView.view removeFromSuperview]; [m_customStartupView removeFromParentViewController]; } }上的数组列上使用explode有一个简单的方法吗？它在Scala中相对简单，但在Java中这个函数似乎不可用（如javadoc中所述）。

一个选项是在查询中使用DataFrame和SQLContext.sql(...)函数，但我正在寻找更好，更清洁的方法。 explode是从镶木地板文件中加载的。

Answer 1

我用这种方式解决了这个问题：假设你有一个包含名为“positions”的职位描述的数组列，对于每个拥有“fullName”的人。

然后你从初始架构得到：

root
|-- fullName: string (nullable = true)
|-- positions: array (nullable = true)
    |    |-- element: struct (containsNull = true)
    |    |    |-- companyName: string (nullable = true)
    |    |    |-- title: string (nullable = true)
...

到架构：

root
 |-- personName: string (nullable = true)
 |-- companyName: string (nullable = true)
 |-- positionTitle: string (nullable = true)

做：

    DataFrame personPositions = persons.select(persons.col("fullName").as("personName"),
          org.apache.spark.sql.functions.explode(persons.col("positions")).as("pos"));

    DataFrame test = personPositions.select(personPositions.col("personName"),
    personPositions.col("pos").getField("companyName").as("companyName"), personPositions.col("pos").getField("title").as("positionTitle"));

Answer 2

似乎可以使用org.apache.spark.sql.functions.explode(Column col)和DataFrame.withColumn(String colName, Column col)的组合将列替换为其分解版本。

SparkSQL并在Java中的DataFrame上爆炸

2 个答案: