Question

我有一个CSV文件以及一个必须通过Spark（2.0.0和Scala 2.11.8）作为数据框读取的标题。

示例csv数据：

Item,No. of items,Place
abc,5,xxx
def,6,yyy
ghi,7,zzz
.........

当我尝试将spark中的csv数据作为数据帧读取时，我遇到了问题，因为标题包含具有特殊字符的列（项目编号）＆＃34;。＆＃34;

我尝试读取csv数据的代码是：

val spark = SparkSession.builder().appName("SparkExample")
import spark.implicits._    
val df = spark.read.option("header", "true").csv("file:///INPUT_FILENAME")

我遇到错误：

Exception in thread "main" org.apache.spark.sql.AnalysisException: Unable to resolve No. of items given [Item,No. of items,Place];

如果我从标题中删除"."，我不会收到任何错误。甚至试图逃避角色，但它甚至从数据中逃脱了所有"."个字符。

有没有办法只使用spark代码从CSV标题中转义特殊字符"."？

Answer 1

@Pooja Nayak，不确定这是否已经解决;为了社区的利益回答这个问题。

sc: SparkContext
spark: SparkSession
sqlContext: SQLContext

// Read the raw file from localFS as-is.
val rdd_raw = sc.textFile("file:///home/xxxx/sample.csv")

// Drop the first line in first partition because it is the header.
val rdd = rdd_raw.mapPartitionsWithIndex{(idx,iter) => 
                      if(idx == 0) iter.drop(1) else iter
}

// A function to create schema dynamically.
def schemaCreator(header: String): StructType = {
  StructType(header
              .split(",")
              .map(field => StructField(field.trim, StringType, true))
  )
}

// Create the schema for the csv that was read and store it.
val csvSchema: StructType = schemaCreator(rdd_raw.first)

// As the input is CSV, split it at "," and trim away the whitespaces.
val rdd_curated = rdd.map(x => x.split(",").map(y => y.trim)).map(xy => Row(xy:_*))

// Create the DF from the RDD.
val df = sqlContext.createDataFrame(rdd_curated, csvSchema)

import是必要的

import org.apache.spark.sql.types._
import org.apache.spark.sql._
import org.apache.spark._

Answer 2

我正在给你一个与pyspark合作的例子，希望同样适用于你，只需添加一些与语言相关的语法。

file =r'C:\Users\e5543130\Desktop\sampleCSV2.csv'   
conf = SparkConf().setAppName('FICBOutputGenerator')
sc = SparkContext(conf=conf)
sc.setLogLevel("ERROR")
sqlContext = SQLContext(sc)
df = sqlContext.read.options(delimiter=",", header="true").csv("cars.csv")   #Without deprecated API
df = sqlContext.read.format("com.databricks.spark.csv").option("header", "true").option("inferSchema", "true").option("delimiter", ",").load("cars.csv")

将csv文件读取为spark数据帧

2 个答案: