Oilfield service vehicles, mechanical displacement meter provers, and roadway striping vehicles exceptions. Hazardous material classes and index to hazard class definitions.Ĭlassification of a material having more than one hazard. This takes about 1 second - sift processed 40 million records / 1 GB of data in just one second.Shippers-General Requirements for Shipments and Packagings
| sift -i '\d+\s+(+).*knicks' -replace '$1' | sort | uniq -c | sort -nr | head This task can be improved by filtering the data for lines containing 'knicks' first and then using the complex regular expression on the results only: Searching for simple strings with sift is very fast due to optimizations in the used algorithms and implementations. While this is not bad, there is much room for improvement.
Sift -i -no-filename '^\d+\s+(+).*knicks' -replace '$1' | sort | uniq -c | sort -nr | head
LOCK CODE IN SIFT HEADS 5 HOW TO
Sift can be used to perform this task easily - this example also shows its flexibility and how to optimize for performance.Ī typical approach might be to solve this with one complex regular expression for sift (and some unix tools): The best performance was achieved with a solution in Ruby (40s) while the Go solution took about 63 seconds to finish. The task was to extract all tweets mentioning 'knicks' from a large dataset (about 40M record / 1 GB) and aggregate them based on the neighborhood of origin. It should be noted that all implementations used a map-reduce approach. The main goal was to compare the implementations while performance was not too important. Sift '(.*?)' -preceded-by bk102 -limit 1 -replace '$1' books.xmlĭimitri Roche published an interesting language comparision for an ETL (extract, transform, load) task. Or (using conditions and limiting results to one match) Sift -m '(.*?)' books.xml -replace 'description="$1"'ĭescription="An in-depth look at creating applications with XML."ĭescription="A former architect battles corporate zombies,Įxtract the author of the book with id 'bk102': The extracted data can easily be transformed to match a desired format: Sift can be used to extract multiline values: Grep 'RecordId' myXmlFile.xml | awk -F">" '' | awk -F"(\d+)' -replace '$1' myXmlFile.xmlĪn in-depth look at creating applications with XML.Ī former architect battles corporate zombies,Īn evil sorceress, and her own childhood to become queen The quite complicated grep+awk combination to extract the RecordId The following examples show some solutions to problems posted in forums/blogs/etc.
Sift was designed with real-world problems in mind. Sift -file-matches 'status: error' '^log:' If you want to search for lines starting with "log:", but only show them if the file contains "status: error", To select which files you want to show matches for (depending on the content of the file).Įxample: a collection of files with system health information, containing log messages and a status field. Restrict recursion to specific directories Only search in files matching a classic GLOB pattern:Įxclude files matching a classic GLOB pattern: Only search in Perl files (*.pl, *.pm, *.pod, *.t or a perl shebang on the first line): The following table shows the different options: Some options provide overlapping functionality - the idea behind this is that less complex filtering options require less typing, while complex filtering selections are still possible. Sift provides various options to select which files you want to search.
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