Hi Richard,
You can use the following to read JSON data into DF. The example is reading
JSON from Kafka topic
val sc = spark.sparkContext
import spark.implicits._
// Use map to create the new RDD using the value portion of the
pair.
val jsonRDD = pricesRDD.map(x => x._2)
// Create DataFrame from jsonRDD
val jsonDF = sqlContext.read.json(jsonRDD)
This is an example of reading a MongoDB document into Spark
dfrddMongoDB.printSchema
/*
root
|-- _id: struct (nullable = true)
| |-- oid: string (nullable = true)
|-- operation: struct (nullable = true)
| |-- op_type: integer (nullable = true)
| |-- op_time: string (nullable = true)
|-- priceInfo: struct (nullable = true)
| |-- key: string (nullable = true)
| |-- ticker: string (nullable = true)
| |-- timeissued: string (nullable = true)
| |-- price: double (nullable = true)
| |-- currency: string (nullable = true)
// one example of mongo document from mongo collection
{
"_id" : ObjectId("5cae4fa25d8b5279db785b43"),
"priceInfo" : {
"key" : "2ca8de24-eaf3-40d4-b0ef-c8b56534ceb5",
"ticker" : "ORCL",
"timeissued" : "2019-04-10T21:20:57",
"price" : 41.13,
"currency" : "GBP"
},
"operation" : {
"op_type" : NumberInt(1),
"op_time" : "1554927506012"
}
}
*/
// Flatten the structs
val df = dfrddMongoDB.
select(
'priceInfo.getItem("key").as("key")
, 'priceInfo.getItem("ticker").as("ticker")
, 'priceInfo.getItem("timeissued").as("timeissued")
, 'priceInfo.getItem("price").as("price")
, 'priceInfo.getItem("currency").as("currency")
, 'operation.getItem("op_type").as("op_type")
, 'operation.getItem("op_time").as("op_time")
)
HTH
Dr Mich Talebzadeh
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On Fri, 19 Jul 2019 at 21:48, Richard <fifistorm...@gmail.com> wrote:
> let's say I use spark to migrate some data from Cassandra table to Oracle
> table
> Cassandra Table:
> CREATE TABLE SOURCE(
> id UUID PRIMARY KEY,
> col1 text,
> col2 text,
> jsonCol text
> );
> example jsonCol value: {"foo": "val1", "bar", "val2"}
>
> I am trying to extract fields from the json column while importing to
> Oracle table
> Destination (
> id varchar2(50),
> col1 varchar(128).
> col2 varchar(128)
> raw_json clob,
> foo varchar2(256),
> bar varchar2(256)
> );
>
> What I have done:
> separate udf for foo and bar.
> This approach works, but that also means I need to deserialize raw json to
> json object twice, things getting worse if i want to extract many fields
> from the json.
> example:
> df = df.withColumn("foo", getFoo.apply(col("jsonCol")))
> .withColumn("bar", getBar.apply(col("jsonCol")));
> // getFoo and getBar are UserDefinedFunction
>
> how do I parse raw json string only once and explode fields I need to
> multiple columns into Oracle in spark?
>
> Thanks,
>
>
>
>
>
>
