Hi guys I am parsing an unstructured file for some key words but i can't seem to easily find the line number of what the results I am getiing
val filePath:String = "myfile"
val myfile = sc.textFile(filePath);
var ora_temp = myfile.filter(line => line.contains("MyPattern")).collect
ora_temp.length
However, I not only want to find the lines that contains MyPatterns but I want more like a tupple (Mypattern line, line number)
Thanks in advance,
You can use ZipWithIndex as eliasah pointed out in a comment (with probably the most succinct way to do this using the direct tuple accessor syntax), or like so using pattern matching in the filter:
val matchingLineAndLineNumberTuples = sc.textFile("myfile").zipWithIndex().filter({
case (line, lineNumber) => line.contains("MyPattern")
}).collect
Related
I want to create a function to handle the text-prepocessing in a problem I am facing with text data. I am familiar with Python and pandas dataframe and my usual thought process of solving the problem is to use a function and then using pandas apply method to apply the function to all the elements in a column. However I don't know where to begin to accomplish this.
So, I created two functions to handle the replacements. The problem is that I don't know how to put more than one replace inside this method. I need to make about 20 replacements for three separate dataframes so to solve it with this method it would take me 60 lines of code. Is there a way to do all the replacements inside a single function and then apply it to all the elements in a dataframe column in scala?
def removeSpecials: String => String = _.replaceAll("$", " ")
def removeSpecials2: String => String = _.replaceAll("?", " ")
val udf_removeSpecials = udf(removeSpecials)
val udf_removeSpecials2 = udf(removeSpecials2)
val consolidated2 = consolidated.withColumn("product_description", udf_removeSpecials($"product_description"))
val consolidated3 = consolidated2.withColumn("product_description", udf_removeSpecials2($"product_description"))
consolidated3.show()
Well you can simply add every replacement next to the previous one like this :
def removeSpecials: String => String = _.replaceAll("$", " ").replaceAll("?", " ")
But in this case where the replacement character is the same, it would be better to use regular expressions to avoid multiple replaceAll.
def removeSpecials: String => String = _.replaceAll("\\$|\\?", " ")
Note that \\ is used as escape character.
I have a text file with the below data having no particular format
abc*123 *180109*1005*^*001*0000001*0*T*:~
efg*05*1*X*005010X2A1~
k7*IT 1234*P*234df~
hig*0109*10052200*Rq~
abc*234*9698*709870*99999*N:~
tng****MI*917937861~
k7*IT 8876*e*278df~
dtp*D8*20171015~
I want the output as two files as below :
Based on string abc, I want to split the file.
file 1:
abc*123 *180109*1005*^*001*0000001*0*T*:~
efg*05*1*X*005010X2A1~
k7*IT 1234*P*234df~
hig*0109*10052200*Rq~
file 2:
abc*234*9698*709870*99999*N:~
tng****MI*917937861~
k7*IT 8876*e*278df~
dtp*D8*20171015~
And the file names should be IT name(the line starts with k7) so file1 name should be IT_1234 second file name should be IT_8876.
There is this little dirty trick that I used for a project :
sc.hadoopConfiguration.set("textinputformat.record.delimiter", "abc")
You can set the delimiter of your spark context for reading files. So you could do something like this :
val delimit = "abc"
sc.hadoopConfiguration.set("textinputformat.record.delimiter", delimit)
val df = sc.textFile("your_original_file.txt")
.map(x => (delimit ++ x))
.toDF("delimit_column")
.filter(col("delimit_column") !== delimit)
Then you can map each element of your DataFrame (or RDD) to be written to a file.
It's a dirty method but it might help you !
Have a good day
PS : The filter at the end is to drop the first line which is empty with the concatenated delimiter
You can benefit from sparkContext's wholeTextFiles function to read the file. Then parse it to separate the strings ( here I have used #### as distinct combination of characters that won't repeat in the text)
val rdd = sc.wholeTextFiles("path to the file")
.flatMap(tuple => tuple._2.replace("\r\nabc", "####abc").split("####")).collect()
And then loop the array to save the texts to output
for(str <- rdd){
//saving codes here
}
I asked the question before but it was unclear so I added more explanation to be more clear and to get help.
replace strings with ZipWithIndex/ZipWithUniqueID
I am trying to map string to number using ZipWithIndex OR ZipWithUniqueID
lets say I have this format
("u1",("name", "John Sam"))
("u2",("age", "twinty Four"))
("u3",("name", "sam Blake"))
I want this result
(0,(3,4))
(1,(5,6))
(2,(3,8))
I tried to use zipWithIndex directly to the triples but I got each letter mapped to a number I want to map the whole string without dividing it.
and tried to extract the first element in the key, value pair
so I did
val first = file.map(line=> line._1).distinct()
then apply ZipWithIndex
val z1= first.ZipWithIndex()
I got result like this
("u1",0)
("u2",1)
("u3",2)
now I need to take the ids/numbers and change it in my original file. and I need to keep all the distinct ids/numbers in hashTable to be able to look for them later on.
is there any way to do that? Any suggestions?
I hope you got my question
You mean something like this?
val file = List(("u1",("name", "John Sam")),
("u2",("age", "twinty Four")),
("u3",("name", "sam Blake")))
val first = file.map(line=> line._1) ++
file.flatMap(line=> List(line._2._1, line._2._2)).distinct
val z1: Map[String,Int] = Map[String,Int](first.zipWithIndex:_*)
file.map{ l =>
(z1(l._1),
(z1(l._2._1), z1(l._2._2)))
}
As I am new to scala ,This problem might look very basic to all..
I have a file called data.txt which contains like below:
xxx.lss.yyy23.com-->mailuogwprd23.lss.com,Hub,12689,14.98904563,1549
xxx.lss.yyy33.com-->mailusrhubprd33.lss.com,Outbound,72996,1.673717588,1949
xxx.lss.yyy33.com-->mailuogwprd33.lss.com,Hub,12133,14.9381027,664
xxx.lss.yyy53.com-->mailusrhubprd53.lss.com,Outbound,72996,1.673717588,3071
I want to split the line and find the records depending upon the numbers in xxx.lss.yyy23.com
val data = io.Source.fromFile("data.txt").getLines().map { x => (x.split("-->"))}.map { r => r(0) }.mkString("\n")
which gives me
xxx.lss.yyy23.com
xxx.lss.yyy33.com
xxx.lss.yyy33.com
xxx.lss.yyy53.com
This is what I am trying to count the exact value...
data.count { x => x.contains("33")}
How do I get the count of records who does not contain 33...
The following will give you the number of lines that contain "33":
data.split("\n").count(a => a.contains("33"))
The reason what you have above isn't working is that you need to split data into an array of strings again. Your previous statement actually concatenates the result into a single string using newline as a separator using mkstring, so you can't really run collection operations like count on it.
The following will work for getting the lines that do not contain "33":
data.split("\n").count(a => !a.contains("33"))
You simply need to negate the contains operation in this case.
Reading lines in a foreach loop, a function looks for a value by a key in a CSV-like structured text file. After a specific line is found, it is senseless to continue reading lines looking for something there. How to stop as there is no break statement in Scala?
Scala's Source class is lazy. You can read chars or lines using takeWhile or dropWhile and the iteration over the input need not proceed farther than required.
To expand on Randall's answer. For instance if the key is in the first column:
val src = Source.fromFile("/etc/passwd")
val iter = src.getLines().map(_.split(":"))
// print the uid for Guest
iter.find(_(0) == "Guest") foreach (a => println(a(2)))
// the rest of iter is not processed
src.close()
Previous answers assumed that you want to read lines from a file, I assume that you want a way to break for-loop by demand.
Here is solution
You can do like this:
breakable {
for (...) {
if (...) break
}
}