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There are several approaches to operate Pig. We’re going to run in MapReduce manner against the area node. MapReduce mode operates versus the HDFS, Which explains why we necessary to import the file during the prior action.
Either download a release or develop a distribution zip as outlined earlier mentioned. Unzip the archive to the wished-for location.
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The XML file really should be copied into a place where by it could be shared with Dash users, plus the tgz file copied to your areas specified in feedLocations.
You should only have to established the javadocTask residence when the job you use to create Javadoc is non-normal. One example is, there might be a task referred to as allJavadoc in a very multi-module
This tends to generate a feed directory within the javadoc2dash.outputLocation Listing. This Listing will comprise an XML file describing the feed
Variety head BX-Publications.csv to find out the very first couple of lines of the Uncooked facts. You’ll detect that’s it’s probably not comma-delimited; the delimiter is ‘;’. You can also find some escaped HTML entities we can easily clean up up, plus the quotations all around each of the values may be removed.
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This is the meat from the operation. The FOREACH loops more than the groupByYear selection, and we Produce values. Our output is outlined applying some values accessible to us inside the FOREACH. We first acquire team, and that is an alias for your grouping benefit and say to put it in our new collection being an product named YearOfPublication.
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You ought to nevertheless have your publications selection outlined if you haven’t exited your Pig session. You'll be able to redefine it conveniently by pursuing the above ways again. Allow’s do a small amount of cleanup on the information this time, nevertheless.
We’ll start with The easy Evaluation of the quantity of publications ended up penned by year. In Hive, This may be accomplished with just one query.