在 Spark 中展平行
Flattening Rows in Spark
我正在使用 scala 对 spark 进行一些测试。我们通常读取 json 个文件,需要像下面的例子一样操作:
test.json:
{"a":1,"b":[2,3]}
val test = sqlContext.read.json("test.json")
如何将其转换为以下格式:
{"a":1,"b":2}
{"a":1,"b":3}
您可以使用explode
函数:
scala> import org.apache.spark.sql.functions.explode
import org.apache.spark.sql.functions.explode
scala> val test = sqlContext.read.json(sc.parallelize(Seq("""{"a":1,"b":[2,3]}""")))
test: org.apache.spark.sql.DataFrame = [a: bigint, b: array<bigint>]
scala> test.printSchema
root
|-- a: long (nullable = true)
|-- b: array (nullable = true)
| |-- element: long (containsNull = true)
scala> val flattened = test.withColumn("b", explode($"b"))
flattened: org.apache.spark.sql.DataFrame = [a: bigint, b: bigint]
scala> flattened.printSchema
root
|-- a: long (nullable = true)
|-- b: long (nullable = true)
scala> flattened.show
+---+---+
| a| b|
+---+---+
| 1| 2|
| 1| 3|
+---+---+
我正在使用 scala 对 spark 进行一些测试。我们通常读取 json 个文件,需要像下面的例子一样操作:
test.json:
{"a":1,"b":[2,3]}
val test = sqlContext.read.json("test.json")
如何将其转换为以下格式:
{"a":1,"b":2}
{"a":1,"b":3}
您可以使用explode
函数:
scala> import org.apache.spark.sql.functions.explode
import org.apache.spark.sql.functions.explode
scala> val test = sqlContext.read.json(sc.parallelize(Seq("""{"a":1,"b":[2,3]}""")))
test: org.apache.spark.sql.DataFrame = [a: bigint, b: array<bigint>]
scala> test.printSchema
root
|-- a: long (nullable = true)
|-- b: array (nullable = true)
| |-- element: long (containsNull = true)
scala> val flattened = test.withColumn("b", explode($"b"))
flattened: org.apache.spark.sql.DataFrame = [a: bigint, b: bigint]
scala> flattened.printSchema
root
|-- a: long (nullable = true)
|-- b: long (nullable = true)
scala> flattened.show
+---+---+
| a| b|
+---+---+
| 1| 2|
| 1| 3|
+---+---+