How to get substring using patterns and replace quotes in json value field using scala? - scala

Question

I have few json messages like
{"column1":"abc","column2":"123","column3":qwe"r"ty,"column4":"abc123"}
{"column1":"defhj","column2":"45","column3":asd"f"gh,"column4":"def12d"}
I need to add double quotes both sides for column3 value and replace double quotes in the column3 value with single quotes using scala.

Answer 1

You have mentioned in the comment above
I have huge dataset in kafka.I am trying to read from kafka and write to hdfs through spark using scala.I am using json parser but unable to parse because of column3 issue.so need to manipulate the message to change into json
So you must be having collecting of malformed jsons as in the question. I have created a list as
val kafkaMsg = List("""{"column1":"abc","column2":"123","column3":qwe"r"ty,"column4":"abc123"}""", """{"column1":"defhj","column2":"45","column3":asd"f"gh,"column4":"def12d"}""")
and you are reading it through Spark so you must be having rdds as
val rdd = sc.parallelize(kafkaMsg)
All you need is some parsing in the malformed text json to make it valid json string as
val validJson = rdd.map(msg => msg.replaceAll("[}\"{]", "").split(",").map(_.split(":").mkString("\"", "\":\"", "\"")).mkString("{", ",", "}"))
validJson should be
{"column1":"abc","column2":"123","column3":"qwerty","column4":"abc123"}
{"column1":"defhj","column2":"45","column3":"asdfgh","column4":"def12d"}
You can create a dataframe from the validJson rdd as
sqlContext.read.json(validJson).show(false)
which should give you
+-------+-------+-------+-------+
|column1|column2|column3|column4|
+-------+-------+-------+-------+
|abc |123 |qwerty |abc123 |
|defhj |45 |asdfgh |def12d |
+-------+-------+-------+-------+
Or you can do as per your requirement.

Answer 2

Goal
add double quotes both sides for column3 value and replace double quotes in the column3 value with single quotes using scala.
I would recommend to use RegEx because you have more flexibility with it.
Here is the solution:
val kafkaMsg = List("""{"column1":"abc","column2":"123","column3":qwe"r"ty,"column4":"abc123"}""", """{"column1":"defhj","column2":"45","column3":asd"f"gh,"column4":"def12d"}""", """{"column1":"defhj","column2":"45","column3":without-quotes,"column4":"def12d"}""")
val rdd = sc.parallelize(kafkaMsg)
val rePattern = """(^\{.*)("column3":)(.*)(,"column4":.*)""".r
val newRdd = rdd.map(r =>
r match {
case rePattern(start, col3, col3Value, end) => (start + col3 + '"' + col3Value.replaceAll("\"", "'") + '"' + end)
case _ => r }
)
newRdd.foreach(println)
Explanation:
First and second statements are rdd initialization.
Third line defines the regex pattern. You may need to adjust it to your situation.
Regex produce 4 groups of values (whatever is in a () is a group):
string starting with "{" and whatever after until we meet "column3":
"column3": itself
whatever comes after "column3": but before ,"column4":
whatever comes starting ,"column4":
I use these 4 groups in next statement.
Iterate over your rdd, run it against regex, and change it: replace double quotes with single, and add open/close quotes. In case there is no match the original string will be returned.
Because regex was defined with 4 groups, I use 4 variables to map matches:
case rePattern(start, col3, col3Value, end) =>
Note: Code doesn't check if you have double quote in the value or not, it just runs update. You can add validation on your own if you need.
Show the results.
Important notes:
Regex that I used is strictly linked to your source string format. Keep in mind that you have JSON, so order of your keys is not guaranteed. As a result you can end up with "column4" (which is used as a column3 value ending) may come before "column3".
If you use comma as a key/value ending, make sure you don't have it as part of column3 value.
Bottom line: you need to adjust my regex to properly identify the end of column3 value.
Hope it helps.