Writing CSV file using Spark and java - handling empty values and quotes

Question

Initial data is in Dataset<Row> and I am trying to write to pipe delimited file and I want each non empty cell and non null values to be placed in quotes. Empty or null values should not contain quotes

result.coalesce(1).write()
            .option("delimiter", "|")
            .option("header", "true")
            .option("nullValue", "")
            .option("quoteAll", "false")
            .csv(Location);

Expected output:

"London"||"UK"
"Delhi"|"India"
"Moscow"|"Russia"

Current Output:

London||UK
Delhi|India
Moscow|Russia

If I change the "quoteAll" to "true", output I am getting is:

"London"|""|"UK"
"Delhi"|"India"
"Moscow"|"Russia"

Spark version is 2.3 and java version is java 8

Answer 1

Java answer. CSV escape is not just adding " symbols around. You should handle " inside strings. So let's use StringEscapeUtils and define UDF that will call it. Then just apply the UDF to each of the column.

import org.apache.commons.text.StringEscapeUtils;
import org.apache.spark.sql.Column;
import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import static org.apache.spark.sql.functions.*;
import org.apache.spark.sql.expressions.UserDefinedFunction;
import org.apache.spark.sql.types.DataTypes;

import java.util.Arrays;

public class Test {

    void test(Dataset<Row> result, String Location) {
        // define UDF
        UserDefinedFunction escape = udf(
            (String str) -> str.isEmpty()?"":StringEscapeUtils.escapeCsv(str), DataTypes.StringType
        );
        // call udf for each column
        Column columns[] = Arrays.stream(result.schema().fieldNames())
                .map(f -> escape.apply(col(f)).as(f))
                .toArray(Column[]::new);

         // save the result
        result.select(columns)
                .coalesce(1).write()
                .option("delimiter", "|")
                .option("header", "true")
                .option("nullValue", "")
                .option("quoteAll", "false")
                .csv(Location);
    }
}

Side note: coalesce(1) is a bad call. It collect all data on one executor. You can get executor OOM in production for huge dataset.