This strains defines the data structure of the fields from the file. We’ll choose to refer back again to it later.
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We've got the outcomes, but how do we see them? We could retail outlet them back into HDFS and extract them like that, or we can easily make use of the DUMP command.
There’s a great deal additional info during the established beyond yrs and publications counts. What if we wanted to see books posted a year by author? Why don’t we go a action farther and group All those outcomes by publisher likewise?
Be aware which i’ve inlined the group generation within the FOREACH assertion. It ought to be apparent that we’re grouping textbooks by author. This statement also introduces the FLATTEN Procedure. We understand that the Team operation makes a collection the place each important corresponds to an index of values; FLATTEN “flattens” this list to produce entries for every record worth.
The set up and configuration of Hadoop and Hive is further than the scope of this article. If you’re just getting started, I would highly suggest grabbing certainly one of Cloudera’s pre-constructed virtual machines that have every little thing you will need.
You’ll see a listing of yrs, combined with the quantity of books for that 12 months. You could possibly discover that many of the values don’t make Significantly perception; there must be no yr 0, nor ought to there be entries for a blank 12 months. We’ll thoroughly clean those problems up in the subsequent Examination.
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Given that We have now the data ready, Allow’s do a megatomi.com thing with it. The easy example is to determine the amount of books had been posted each year. We’ll start with that, then find out if we could do a little bit far more.
The AS clause defines how the fields from the file are mapped into Pig info kinds. You’ll see that we remaining off every one of the “Graphic-URL-XXX” fields; we don’t will need them for Assessment, and Pig will ignore fields that we don’t notify it to load.
I’m assuming that you will be working the following techniques using the Cloudera VM, logged in as being the cloudera user. If the setup differs, change appropriately.
You need to even now have your guides collection defined in case you haven’t exited your Pig session. It is possible to redefine it easily by next the above mentioned actions again. Allow’s do a small amount of cleanup on the information this time, however.
Kind head BX-Textbooks.csv to see the very first couple lines with the Uncooked information. You’ll detect that’s it’s not likely comma-delimited; the delimiter is ‘;‘. You will also find some escaped HTML entities we can easily clear up, plus the estimates close to every one of the values may be eliminated.