I have following input:
(A,123#3A,B,C,D,134#wer,E,242#wer)
Is there a way to to get following output using filter/replace/trim or any other function.
(A,123,B,C,D,134,E,242)
Your question is not completely clear.
If you mean that your input is a list of strings then you can do:
val input = Seq("A","123#3A","B","C","D","134#wer","E","242#wer")
input.map(_.split("#").head)
but if you mean that your input it one string then you can do:
val input2 = "(A,123#3A,B,C,D,134#wer,E,242#wer)"
val Pattern = "\\(([a-zA-Z\\d,#]*)\\)".r
input2 match {
case Pattern(str) => "(" + str.split(",").map(_.split("#").head).mkString(",") + ")"
}
Related
I has a CSV file.
This is my Input:
a _ \_ \ b_c b\_c "
Now, I want to convert a space delimited file to a CSV file. What should I do?
Fields not specified are considered "String 0" and are not enclosed
in quotes.
This is Specifications:
1.The string "_" by itself is converted to a null string.
( -n option changes "_" )
2.The string \c is converted to c.
3.The backslash character \ by itself is converted to a space
4.The underscore is converted to a space if it occurs in a string.
( -s option changes "_" )
5.\n at the end of a line is converted automatically to \r\n.
6.Within String 1, " is converted to "".
I want to have the desired output result as below. Please help me.
"a","","_"," ","b c","b_c",""""
The requirements are a little bit confusing to me, but you can try with this (which produces the expected output):
import scala.util.matching.Regex
val input = "a _ \\_ \\ b_c b\\_c \""
// List of replacements required (first replacement will be apply first)
val replacements: List[(Regex, String)] = List(
("""^_$""".r, ""),
("""(?<!\\)_""".r, " "),
("""\\(.)""".r, "$1"),
("""\\""".r, " "),
(""""""".r, "\"\""))
def applyReplacements(inputString: String, replacements: List[(Regex, String)]): String =
replacements match {
case Nil =>
inputString
case replacement :: tail =>
applyReplacements(
replacement._1.replaceAllIn(inputString, replacement._2),
tail)
}
def processLine(input: String): String = {
val inputArray = input.split(" ")
val outputArray = inputArray.map(x => applyReplacements(x, replacements))
val finalLine = outputArray.map(x => s"""\"${x}\"""").mkString(",")
// Use s"${finalLine}\r\n" instead if you need the '\r\n' ending
finalLine
}
processLine(input)
// output:
// String = "a","","_"," ","b c","b_c",""""
Probably you will have to apply some modifications to fully adapt it to your requirements (which are not fully clear to me).
If you need to apply this over a Spark RDD, you will have to put processLine in a map so that it processes every line in the RDD.
Hope it helps.
I have an array
val a = "((x1,x2),(y1,y2),(z1,z2))"
I want to parse this into a scala array
val arr = Array(("x1","x2"),("y1","y2"),("z1","z2"))
Is there a way of directly doing this with an expr() equivalent ?
If not how would one do this using split
Note : x1 x2 x3 etc are strings and can contain special characters so key would be to use () delimiters to parse data -
Code I munged from Dici and Bogdan Vakulenko
val x2 = a.getString(1).trim.split("[\()]").grouped(2).map(x=>x(0).trim).toArray
val x3 = x2.drop(1) // first grouping is always null dont know why
var jmap = new java.util.HashMap[String, String]()
for (i<-x3)
{
val index = i.lastIndexOf(",")
val fv = i.slice(0,index)
val lv = i.substring(index+1).trim
jmap.put(fv,lv)
}
This is still suceptible to "," in the second string -
Actually, I think regex are the most convenient way to solve this.
val a = "((x1,x2),(y1,y2),(z1,z2))"
val regex = "(\\((\\w+),(\\w+)\\))".r
println(
regex.findAllMatchIn(a)
.map(matcher => (matcher.group(2), matcher.group(3)))
.toList
)
Note that I made some assumptions about the format:
no whitespaces in the string (the regex could easily be updated to fix this if needed)
always tuples of two elements, never more
empty string not valid as a tuple element
only alphanumeric characters allowed (this also would be easy to fix)
val a = "((x1,x2),(y1,y2),(z1,z2))"
a.replaceAll("[\\(\\) ]","")
.split(",")
.sliding(2)
.map(x=>(x(0),x(1)))
.toArray
I have a string as
something,'' something,nothing_something,op nothing_something,'' cat,cat
I want to achieve my output as
'' something,op nothing_something,cat
Is there any way to achieve it?
If I understand your requirement correctly, here's one approach with the following steps:
Split the input string by "," and create a list of indexed-CSVs and convert it to a Map
Generate 2-combinations of the indexed-CSVs
Check each of the indexed-CSV pairs and capture the index of any CSV which is contained within the other CSV
Since the CSVs corresponding to the captured indexes are contained within some other CSV, removing these indexes will result in remaining indexes we would like to keep
Use the remaining indexes to look up CSVs from the CSV Map and concatenate them back to a string
Here is sample code applying to a string with slightly more general comma-separated values:
val str = "cats,a cat,cat,there is a cat,my cat,cats,cat"
val csvIdxList = (Stream from 1).zip(str.split(",")).toList
val csvMap = csvIdxList.toMap
val csvPairs = csvIdxList.combinations(2).toList
val csvContainedIdx = csvPairs.collect{
case List(x, y) if x._2.contains(y._2) => y._1
case List(x, y) if y._2.contains(x._2) => x._1
}.
distinct
// csvContainedIdx: List[Int] = List(3, 6, 7, 2)
val csvToKeepIdx = (1 to csvIdxList.size) diff csvContainedIdx
// csvToKeepIdx: scala.collection.immutable.IndexedSeq[Int] = Vector(1, 4, 5)
val strDeduped = csvToKeepIdx.map( csvMap.getOrElse(_, "") ).mkString(",")
// strDeduped: String = cats,there is a cat,my cat
Applying the above to your sample string something,'' something,nothing_something,op nothing_something would yield the expected result:
strDeduped: String = '' something,op nothing_something
First create an Array of words separated by commas using split command on the given String, and do other operations using filter and mkString as below:
s.split(",").filter(_.contains(' ')).mkString(",")
In Scala REPL:
scala> val s = "something,'' something,nothing_something,op nothing_something"
s: String = something,'' something,nothing_something,op nothing_something
scala> s.split(",").filter(_.contains(' ')).mkString(",")
res27: String = '' something,op nothing_something
As per Leo C comment, I tested it as below with some other String:
scala> val s = "something,'' something anything anything anything anything,nothing_something,op op op nothing_something"
s: String = something,'' something anything anything anything anything,nothing_something,op op op nothing_something
scala> s.split(",").filter(_.contains(' ')).mkString(",")
res43: String = '' something anything anything anything anything,op op op nothing_something
Following is my code that I have used to convert Iterator[char] to Seq[String].
val result = IOUtils.toByteArray(new FileInputStream (new File(fileDir)))
val remove_comp = result.grouped(11).map{arr => arr.update(2, 32);arr}.flatMap{arr => arr.update(3, 32); arr}
val convert_iter = remove_comp.map(_.toChar.toString).toSeq.mkString.split("\n")
val rdd_input = Spark.sparkSession.sparkContext.parallelize(convert_iter)
val fileDir:
12**34567890
12##34567890
12!!34567890
12¬¬34567890
12
'34567890
I am not happy with this code as the data size is big and converting to string would end up with heap space.
val convert_iter = remove_comp.map(_.toChar)
convert_iter: Iterator[Char] = non-empty iterator
Is there a better way of coding?
By completely disregarding corner cases about empty Strings etc I would start with something like:
val test = Iterable('s','f','\n','s','d','\n','s','v','y')
val (allButOne, last) = test.foldLeft( (Seq.empty[String], Seq.empty[Char]) ) {
case ((strings, chars), char) =>
if (char == '\n')
(strings :+ chars.mkString, Seq.empty)
else
(strings, chars :+ char)
}
val result = allButOne :+ last.mkString
I am sure it could be made more elegant, and handle corner cases better (once you define you want them handled), but I think it is a nice starting point.
But to be honest I am not entirely sure what you want to achieve. I just guessed that you want to group chars divided by \n together and turn them into Strings.
Looking at your code, I see that you are trying to replace the special characters such as **, ## and so on from the file that contains following data
12**34567890
12##34567890
12!!34567890
12¬¬34567890
12
'34567890
For that you can just read the data using sparkContext textFile and use regex replaceAllIn
val pattern = new Regex("[¬~!##$^%&*\\(\\)_+={}\\[\\]|;:\"'<,>.?` /\\-]")
val result = sc.textFile(fileDir).map(line => pattern.replaceAllIn(line, ""))
and you should have you result as RDD[String] which also an iterator
1234567890
1234567890
1234567890
1234567890
12
34567890
Updated
If there are \n and \r in between the texts at 3rd and 4th place and if the result is all fixed length of 10 digits text then you can use wholeTextFiles api of sparkContext and use following regex as
val pattern = new Regex("[¬~!##$^%&*\\(\\)_+={}\\[\\]|;:\"'<,>.?` /\\-\r\n]")
val result = sc.wholeTextFiles(fileDir).flatMap(line => pattern.replaceAllIn(line._2, "").grouped(10))
You should get the output as
1234567890
1234567890
1234567890
1234567890
1234567890
I hope the answer is helpful
How do I remove empty data frames from a sequence of data frames? In this below code snippet, there are many empty data frames in twoColDF. Also another question for the below for loop, is there a way that I can make this efficient? I tried rewriting this to below line but didn't work
//finalDF2 = (1 until colCount).flatMap(j => groupCount(j).map( y=> finalDF.map(a=>a.filter(df(cols(j)) === y)))).toSeq.flatten
var twoColDF: Seq[Seq[DataFrame]] = null
if (colCount == 2 )
{
val i = 0
for (j <- i + 1 until colCount) {
twoColDF = groupCount(j).map(y => {
finalDF.map(x => x.filter(df(cols(j)) === y))
})
}
}finalDF = twoColDF.flatten
Given a set of DataFrames, you can access each DataFrame's underlying RDD and use isEmpty to filter out the empty ones:
val input: Seq[DataFrame] = ???
val result = input.filter(!_.rdd.isEmpty())
As for your other question - I can't understand what your code tries to do, but I'd first try to convert it into something more functional (remove use of vars and imperative conditionals). If I'm guessing the meaning of your inputs, here's something that might be equivalent to what you're trying to do:
var input: Seq[DataFrame] = ???
// map of column index to column values -
// for each combination we'd want a new DF where that column has that value
// I'm assuming values are Strings, can be anything else
val groupCount: Map[Int, Seq[String]] = ???
// for each combination of DF + column + value - produce the filtered DF where this column has this value
val perValue: Seq[DataFrame] = for {
df <- input
index <- groupCount.keySet
value <- groupCount(index)
} yield df.filter(col(df.columns(index)) === value)
// remove empty results:
val result: Seq[DataFrame] = perValue.filter(!_.rdd.isEmpty())