使用数据类型 map<string,bigint> 将数据帧写入 csv在火花 [英] Write dataframe to csv with datatype map&lt;string,bigint&gt; in Spark

问题描述

我有一个文件 file1snappy.parquet.它有一个复杂的数据结构，比如地图，里面的数组.处理后我得到了最终结果.在将结果写入 csv 时，我收到一些错误说

I have a file which is file1snappy.parquet. It is having a complex data structure like a map, array inside that.After processing that I got final result.while writing that results to csv I am getting some error saying

"Exception in thread "main" java.lang.UnsupportedOperationException: CSV data source does not support map<string,bigint> data type."

我使用过的代码:

val conf=new SparkConf().setAppName("student-example").setMaster("local")
    val sc = new SparkContext(conf)
    val sqlcontext = new org.apache.spark.sql.SQLContext(sc)
    val datadf = sqlcontext.read.parquet("C:\\file1.snappy.parquet")
    def sumaggr=udf((aggr: Map[String, collection.mutable.WrappedArray[Long]]) => if (aggr.keySet.contains("aggr")) aggr("aggr").sum else 0)
datadf.select(col("neid"),sumaggr(col("marks")).as("sum")).filter(col("sum") =!= 0).show(false)
    datadf.write.format("com.databricks.spark.csv").option("header", "true").save("C:\\myfile.csv")

我尝试转换 datadf.toString() 但仍然面临同样的问题.如何将该结果写入 CSV.

I tried converting datadf.toString() but still I am facing same issue. How can write that result to CSV.

spark 2.1.1 版

spark version 2.1.1

推荐答案

Spark CSV source 仅支持原子类型.您不能存储任何非原子列

Spark CSV source supports only atomic types. You cannot store any columns that are non-atomic

我认为最好为具有 map 作为数据类型的列创建一个 JSON，并将其保存在 csv 中，如下所示.

I think best is to create a JSON for the column that has map<string,bigint> as a datatype and save it in csv as below.

import spark.implicits._ 
import org.apache.spark.sql.functions._

datadf.withColumn("column_name_with_map_type", to_json(struct($"column_name_with_map_type"))).write.csv("outputpath")

希望这会有所帮助！

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