I'm trying to compare two datasets by looking at the address attribute string used in both datasets and find the fuzzy matching ratios. The read process was fast and read the 350,000 records in dataset 1 and the 14,000 records in dataset 2 in less than a minute. I then sort both lists separately and then use the FuzzyStringCompareFrom2Datasets transformer. I have been running this workspace all day (about 5 hours so far) and it has only output 288 records. Is there a way to speed this up?
Best answer by paalped
FuzzyStringCompare2datsets does not look to support those big datasets, cause what is does it takes for every feature of your 350 000 features and adds a list of 14 000 features it the searches through that list and compare each string to the string to the string attribute you choose to compare(which equals to approx 4 900 000 000 comparison), then it sorts every list ( 350 000 times its sorts a list of length 14 000) by its ratio, and chooses the one with greates accuracy. this will of course be very time consuming with the sizes you are operating with.
How large are the strings that you're comparing using the FuzzyStringCompare?
Which format are you writing to?
What happens if you disable the writer?
Also, do you really need the two Sorters?
+5FuzzyStringCompare2datsets does not look to support those big datasets, cause what is does it takes for every feature of your 350 000 features and adds a list of 14 000 features it the searches through that list and compare each string to the string to the string attribute you choose to compare(which equals to approx 4 900 000 000 comparison), then it sorts every list ( 350 000 times its sorts a list of length 14 000) by its ratio, and chooses the one with greates accuracy. this will of course be very time consuming with the sizes you are operating with.
How large are the strings that you're comparing using the FuzzyStringCompare?
Which format are you writing to?
What happens if you disable the writer?
Also, do you really need the two Sorters?
FuzzyStringCompare2datsets does not look to support those big datasets, cause what is does it takes for every feature of your 350 000 features and adds a list of 14 000 features it the searches through that list and compare each string to the string to the string attribute you choose to compare(which equals to approx 4 900 000 000 comparison), then it sorts every list ( 350 000 times its sorts a list of length 14 000) by its ratio, and chooses the one with greates accuracy. this will of course be very time consuming with the sizes you are operating with.
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