Efficient Grouping and Summing in Linux: A Guide to Streamlining Your Operations（linux分组求和）
Grouping and Summing in Linux is an essential task for many programmers and systems administrators. It is used to quickly and easily organize, summarize, and manipulate data. If not done correctly, it can be a time-consuming and error-prone task. It is important to use efficient methods that utilize the Linux kernel and other tools to streamline operations.
When working with large datasets, it is important to use command-line tools to summarize and format data in a succinct and uniform way. For example, using the ‘sort’ command, it is possible to quickly sort data based on a variety of criteria. This can be used to quickly generate reports or summaries that compare or contrast various elements or groups of data.
The ‘awk’ command-line tool can be used to quickly parse data into various groups and summarize or manipulate it. Awk supports a wide range of features and can be used to search through files or directories, output the results to terminal or files, and sum or calculate the values of data based on criteria. For example, the following ‘awk` command sums the total amount of sales for each customer from a given data set:
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awk ‘ { num = $2 + $3 + $4 + $5; print $1, num}’ sales.tsv
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The ‘cut’ command is an effective tool for quickly selecting and filtering text-based data. This can be used to quickly extract relevant data from files or streams and output the filtered data to a specific file, terminal screen, or other medium. The following ‘cut` command will display the total amount for sales for each customer by only displaying columns two through five and adding them together:
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cut -d ‘,’ -f 2-5 sales.txt | awk ‘{num= $2+$3+$4+$5; print $1, num}’
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Finally, the ‘uniq’ command is an effective way of quickly filtering out duplicated data. This command takes the output of another command and removes any lines that are exact duplicates of one another. This can be used in conjunction with commands such as ‘sort’ and ‘cut’ to quickly eliminate redundant data, or simplify a series of operations that involve deduplicating data.
Although these commands can be used separately, as part of a script, or in combination with other commands, they are a few of the most efficient methods for grouping and summarizing data in Linux. Carefully lifting batches of data, managing and manipulating data regions, and removing duplicate text-based data are all vital operations that utilize the aforementioned and other Linux-based tools. Using these methods, the Linux user can quickly and efficiently manipulate data.
