Spark SQL provides spark.read.json("path") to read a single line and multiline (multiple lines) JSON file into Spark DataFrame and dataframe.write.json("path") to save or write to JSON file, In this tutorial, you will learn how to read a single file, multiple files, all files from a directory into DataFrame and writing DataFrame back to JSON file using Scala example.
Json data in a single Line
[{"empno":"7369","ename":"SMITH","designation":"CLERK","manager":"7902","hire_date":"12/17/1980","sal":"800","deptno":"20" },{"empno":"7499","ename":"ALLEN","designation":"SALESMAN","manager":"7698","hire_date":"2/20/1981","sal":"1600","deptno":"30"},{"empno":"7521","ename":"WARD","designation":"SALESMAN","manager":"7698","hire_date":"2/22/1981","sal":"1250","deptno":"30" },{"empno":"7566","ename":"TURNER","designation":"MANAGER","manager":"7839","hire_date":"4/2/1981","sal":"2975","deptno":"20"},{"empno":"7654","ename":"MARTIN","designation":"SALESMAN","manager":"7698","hire_date":"9/28/1981","sal":"1250","deptno":"30"},{"empno":"7698","ename":"MILLER","designation":"MANAGER","manager":"7839","hire_date":"5/1/1981","sal":"2850","deptno":"30"},{"empno":"7782","ename":"CLARK","designation":"MANAGER","manager":"7839","hire_date":"6/9/1981","sal":"2450","deptno":"10"},{"empno":"7788","ename":"SCOTT","designation":"ANALYST","manager":"7566","hire_date":"12/9/1982","sal":"3000","deptno":"20"},{"empno":"7839","ename":"KING","designation":"PRESIDENT","manager":"NULL","hire_date":"11/17/1981","sal":"5000","deptno":"10"}]
Read single Line Json File
val df = spark.read.json("/FileStore/tables/employees_singleLine.json")
df.show
Json data in a multi Line[
{
"empno":"7369",
"ename":"SMITH",
"designation":"CLERK",
"manager":"7902",
"hire_date":"12/17/1980",
"sal":"800",
"deptno":"20"
},
{
"empno":"7499",
"ename":"ALLEN",
"designation":"SALESMAN",
"manager":"7698",
"hire_date":"2/20/1981",
"sal":"1600",
"deptno":"30"
},
{
"empno":"7521",
"ename":"WARD",
"designation":"SALESMAN",
"manager":"7698",
"hire_date":"2/22/1981",
"sal":"1250",
"deptno":"30"
},
{
"empno":"7566",
"ename":"TURNER",
"designation":"MANAGER",
"manager":"7839",
"hire_date":"4/2/1981",
"sal":"2975",
"deptno":"20"
},
{
"empno":"7654",
"ename":"MARTIN",
"designation":"SALESMAN",
"manager":"7698",
"hire_date":"9/28/1981",
"sal":"1250",
"deptno":"30"
},
{
"empno":"7698",
"ename":"MILLER",
"designation":"MANAGER",
"manager":"7839",
"hire_date":"5/1/1981",
"sal":"2850",
"deptno":"30"
},
{
"empno":"7782",
"ename":"CLARK",
"designation":"MANAGER",
"manager":"7839",
"hire_date":"6/9/1981",
"sal":"2450",
"deptno":"10"
},
{
"empno":"7788",
"ename":"SCOTT",
"designation":"ANALYST",
"manager":"7566",
"hire_date":"12/9/1982",
"sal":"3000",
"deptno":"20"
},
{
"empno":"7839",
"ename":"KING",
"designation":"PRESIDENT",
"manager":"NULL",
"hire_date":"11/17/1981",
"sal":"5000",
"deptno":"10"
}
]
Read Multi Line Json File
val df = spark.read.option("multiline","true").json("/FileStore/tables/employees_multiLine.json")
df.show
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)
Json data in a single Line
[{"empno":"7369","ename":"SMITH","designation":"CLERK","manager":"7902","hire_date":"12/17/1980","sal":"800","deptno":"20" },{"empno":"7499","ename":"ALLEN","designation":"SALESMAN","manager":"7698","hire_date":"2/20/1981","sal":"1600","deptno":"30"},{"empno":"7521","ename":"WARD","designation":"SALESMAN","manager":"7698","hire_date":"2/22/1981","sal":"1250","deptno":"30" },{"empno":"7566","ename":"TURNER","designation":"MANAGER","manager":"7839","hire_date":"4/2/1981","sal":"2975","deptno":"20"},{"empno":"7654","ename":"MARTIN","designation":"SALESMAN","manager":"7698","hire_date":"9/28/1981","sal":"1250","deptno":"30"},{"empno":"7698","ename":"MILLER","designation":"MANAGER","manager":"7839","hire_date":"5/1/1981","sal":"2850","deptno":"30"},{"empno":"7782","ename":"CLARK","designation":"MANAGER","manager":"7839","hire_date":"6/9/1981","sal":"2450","deptno":"10"},{"empno":"7788","ename":"SCOTT","designation":"ANALYST","manager":"7566","hire_date":"12/9/1982","sal":"3000","deptno":"20"},{"empno":"7839","ename":"KING","designation":"PRESIDENT","manager":"NULL","hire_date":"11/17/1981","sal":"5000","deptno":"10"}]
Read single Line Json File
val df = spark.read.json("/FileStore/tables/employees_singleLine.json")
df.show
Json data in a multi Line[
{
"empno":"7369",
"ename":"SMITH",
"designation":"CLERK",
"manager":"7902",
"hire_date":"12/17/1980",
"sal":"800",
"deptno":"20"
},
{
"empno":"7499",
"ename":"ALLEN",
"designation":"SALESMAN",
"manager":"7698",
"hire_date":"2/20/1981",
"sal":"1600",
"deptno":"30"
},
{
"empno":"7521",
"ename":"WARD",
"designation":"SALESMAN",
"manager":"7698",
"hire_date":"2/22/1981",
"sal":"1250",
"deptno":"30"
},
{
"empno":"7566",
"ename":"TURNER",
"designation":"MANAGER",
"manager":"7839",
"hire_date":"4/2/1981",
"sal":"2975",
"deptno":"20"
},
{
"empno":"7654",
"ename":"MARTIN",
"designation":"SALESMAN",
"manager":"7698",
"hire_date":"9/28/1981",
"sal":"1250",
"deptno":"30"
},
{
"empno":"7698",
"ename":"MILLER",
"designation":"MANAGER",
"manager":"7839",
"hire_date":"5/1/1981",
"sal":"2850",
"deptno":"30"
},
{
"empno":"7782",
"ename":"CLARK",
"designation":"MANAGER",
"manager":"7839",
"hire_date":"6/9/1981",
"sal":"2450",
"deptno":"10"
},
{
"empno":"7788",
"ename":"SCOTT",
"designation":"ANALYST",
"manager":"7566",
"hire_date":"12/9/1982",
"sal":"3000",
"deptno":"20"
},
{
"empno":"7839",
"ename":"KING",
"designation":"PRESIDENT",
"manager":"NULL",
"hire_date":"11/17/1981",
"sal":"5000",
"deptno":"10"
}
]
Read Multi Line Json File
val df = spark.read.option("multiline","true").json("/FileStore/tables/employees_multiLine.json")
df.show
Read Multi Line Json File
{
"user": "gT35Hhhre9m",
"dates": ["2016-01-29", "2016-01-28"],
"status": "OK",
"reason": "some reason",
"content": [{
"foo": 123,
"bar": "val1"
}, {
"foo": 456,
"bar": "val2"
}, {
"foo": 789,
"bar": "val3"
}, {
"foo": 124,
"bar": "val4"
}, {
"foo": 126,
"bar": "val5"
}]
}
"user": "gT35Hhhre9m",
"dates": ["2016-01-29", "2016-01-28"],
"status": "OK",
"reason": "some reason",
"content": [{
"foo": 123,
"bar": "val1"
}, {
"foo": 456,
"bar": "val2"
}, {
"foo": 789,
"bar": "val3"
}, {
"foo": 124,
"bar": "val4"
}, {
"foo": 126,
"bar": "val5"
}]
}
val df = spark.read.option("multiline","true").json("/FileStore/tables/data.json")
df.show
df.show
Write data in Json File
df2.write.json("/tmp/spark_output/zipcodes.json")
Processing the JSON files
JSON
is a data interchange format, developed from Javascript. JSON actually
stands for JavaScript Object Notation. It is a text-based format, and
can be expressed,for instance, as XML. The following example uses the
SQL context method called jsonFile to load the HDFS-based JSON data file
named device.json .
The resulting data is created as a data frame:
val dframe = sqlContext.jsonFile("hdfs:///data/spark/device.json")
val dframe = sqlContext.jsonFile("hdfs:///data/spark/device.json")
First, the Apache Spark and Spark SQL classes are imported:
import org.apache.spark._
import org.apache.spark.SparkContext._
import org.apache.spark.sql.Row;
import org.apache.spark.sql.types.{StructType,StructField,StringType};
object sql1 {
def main(args: Array[String]) {
val appName = "sql example 1"
val conf = new SparkConf()
conf.setAppName(appName)
val sc = new SparkContext(conf)
val sqlContext = new org.apache.spark.sql.SQLContext(sc)
val rawRdd = sc.textFile("hdfs:///data/spark/sql/adult.test.data_1x")
val schemaString = "age workclass fnlwgt education " +
"educational-num marital-status occupation relationship " +
"race gender capital-gain capital-loss hours-per-week " +
"native-country income"
val schema =
StructType(schemaString.split(" ").map(fieldName => StructField(fieldName,StringType, true)))
val rowRDD = rawRdd.map(_.split(","))
.map(p => Row( p(0),p(1),p(2),p(3),p(4),p(5),p(6),p(7),p(8),p(9),p(10),p(11),p(12),p(13),p(14) ))
val adultDataFrame = sqlContext.createDataFrame(rowRDD, schema)
val jsonData = adultDataFrame.toJSON
jsonData.saveAsTextFile("hdfs:///data/spark/sql/adult.json")
} // end main
} // end sql1
So
the resulting data can be seen on HDFS, the Hadoop file system ls
command below shows that the data resides in the target directory as a
success file and two part files.
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