Hi Spark Users Group,
I have a csv file to analysis with Spark, but I’m troubling with importing
as DataFrame.
Here’s the minimal reproducible example. Suppose I’m having a
*10(rows)x2(cols)* *space-delimited csv* file, shown as below:
1446566430 2015-11-04<SP>00:00:30
1446566430 2015-11-04<SP>00:00:30
1446566430 2015-11-04<SP>00:00:30
1446566430 2015-11-04<SP>00:00:30
1446566430 2015-11-04<SP>00:00:30
1446566431 2015-11-04<SP>00:00:31
1446566431 2015-11-04<SP>00:00:31
1446566431 2015-11-04<SP>00:00:31
1446566431 2015-11-04<SP>00:00:31
1446566431 2015-11-04<SP>00:00:31
the <SP> in column 2 represents sub-delimiter within that column, and this
file is stored on HDFS, let’s say the path is hdfs:///tmp/1.csv
I’m using *spark-csv* to import this file as Spark *DataFrame*:
sqlContext.read.format("com.databricks.spark.csv")
.option("header", "false") // Use first line of all files as header
.option("inferSchema", "false") // Automatically infer data types
.option("delimiter", " ")
.load("hdfs:///tmp/1.csv")
.show
Oddly, the output shows only a part of each column:
[image: Screenshot from 2016-02-07 15-27-51.png]
and even the boundary of the table wasn’t shown correctly. I also used the
other way to read csv file, by sc.textFile(...).map(_.split(" ")) and
sqlContext.createDataFrame, and the result is the same. Can someone point
me out where I did it wrong?
—
BR,
Todd Leo
