display records which exist in file2 but not in file1
log file1开发者_运维问答 contains records of customers(name,id,date) who visited yesterday log file2 contains records of customers(name,id,date) who visited today
How would you display customers who visited yesterday but not today?
Constraint is: Don't use auxiliary data structure because file contains millions of records. [So, no hashes] Is there a way to do this using Unix commands ??
an example, but check the man page of comm
for the option you want.
comm -2 <(sort -u yesterday) <(sort -u today)
The other tool you can use is diff
diff <(sort -u yesterday) <(sort -u today)
I was personally going for the creating a data structure and records of visits, but, I can see how you'd do it another way too.
In pseudocode, that looks something like python but could be re-written in perl or shell script or ...
import subprocess
import os
for line in fileinput.input(['myfile'])::
# split out data. For the sake of it I'm assuming name\tid\tdate
fields = line.split("\")
id = fields[1]
grepresult = subprocess.Popen("grep \"" + id + "\" file1", shell=True, bufsize=bufsize, stdout=PIPE).stdout
if len(grepresult) == 0:
print fields # it wasn't in field1
That's not perfect, not tested so treat appropriately but it gives you the gist of how you'd use unix commands. That said, as sfussenegger points out C/C++ if that's what you're using should be able to handle pretty large files.
Disclaimer: this is a not so neat solution (repeatedly calling grep) to match the requirements of the question. If I was doing it, I would use C.
Is a customer identified by id? Is it an int or long? If the answer to both questions is yes, an array with 10,000,000 integers shouldn't take more than 10M*4 = 40MB memory - not a big deal on decent hardware. Simply sort and compare them.
btw, sorting an array with 10M random ints takes less than 2 seconds on my machine - again, nothing to be afraid of.
Here's some very simple Java code:
public static void main(final String args[]) throws Exception {
// elements in each log file
int count = 10000000;
// "read" our log file
Random r = new Random();
int[] a1 = new int[count];
int[] a2 = new int[count];
for (int i = 0; i < count; i++) {
a1[i] = Math.abs(r.nextInt());
a2[i] = Math.abs(r.nextInt());
}
// start timer
long start = System.currentTimeMillis();
// sort logs
Arrays.sort(a1);
Arrays.sort(a2);
// counters for each array
int i1 = 0, i2 = 0, i3 = 0;
// initial values
int n1 = a1[0], n2 = a2[0];
// result array
int[] a3 = new int[count];
try {
while (true) {
if (n1 == n2) {
// we found a match, save value if unique and increment counters
if (i3 == 0 || a3[i3-1] != n1) a3[i3++] = n1;
n1 = a1[i1++];
n2 = a2[i2++];
} else if (n1 < n2) {
// n1 is lower, increment counter (next value is higher)
n1 = a1[i1++];
} else {
// n2 is lower, increment counter (next value is higher)
n2 = a2[i2++];
}
}
} catch (ArrayIndexOutOfBoundsException e) {
// don't try this at home - it's not the pretties way to leave the loop!
}
// we found our results
System.out.println(i3 + " commont clients");
System.out.println((System.currentTimeMillis() - start) + "ms");
}
result
// sample output on my machine:
46308 commont clients
3643ms
as you see, quite efficient for 10M records in each log
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