Hi, Thanks for the response. But I could not see fillna function in DataFrame class.
[cid:[email protected]] Is it available in some specific version of Spark sql. This is what I have in my pom.xml <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-sql_2.10</artifactId> <version>1.3.1</version> </dependency> Regards, Anand.C From: ayan guha [mailto:[email protected]] Sent: Monday, May 18, 2015 5:19 PM To: Chandra Mohan, Ananda Vel Murugan; user Subject: Re: Spark sql error while writing Parquet file- Trying to write more fields than contained in row Hi Give a try with dtaFrame.fillna function to fill up missing column Best Ayan On Mon, May 18, 2015 at 8:29 PM, Chandra Mohan, Ananda Vel Murugan <[email protected]<mailto:[email protected]>> wrote: Hi, I am using spark-sql to read a CSV file and write it as parquet file. I am building the schema using the following code. String schemaString = "a b c"; List<StructField> fields = new ArrayList<StructField>(); MetadataBuilder mb = new MetadataBuilder(); mb.putBoolean("nullable", true); Metadata m = mb.build(); for (String fieldName: schemaString.split(" ")) { fields.add(new StructField(fieldName,DataTypes.DoubleType,true, m)); } StructType schema = DataTypes.createStructType(fields); Some of the rows in my input csv does not contain three columns. After building my JavaRDD<Row>, I create data frame as shown below using the RDD and schema. DataFrame darDataFrame = sqlContext.createDataFrame(rowRDD, schema); Finally I try to save it as Parquet file darDataFrame.saveAsParquetFile("/home/anand/output.parquet”) I get this error when saving it as Parquet file java.lang.IndexOutOfBoundsException: Trying to write more fields than contained in row (3 > 2) I understand the reason behind this error. Some of my rows in Row RDD does not contain three elements as some rows in my input csv does not contain three columns. But while building the schema, I am specifying every field as nullable. So I believe, it should not throw this error. Can anyone help me fix this error. Thank you. Regards, Anand.C -- Best Regards, Ayan Guha
