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split: Splits a file into pieces sum: Checksums and counts the blocks in a file tac: Concatenates and prints files in reverse order line by line tail: Outputs the last part of files tr: Translates or deletes characters tsort: Performs a topological sort: unexpand: Converts spaces to tabs uniq: Removes duplicate lines from a sorted file wc
The csplit command in Unix and Unix-like operating systems is a utility that is used to split a file into two or more smaller files determined by context lines. History [ edit ]
The split command first appeared in Version 3 Unix [1] and is part of the X/Open Portability Guide since issue 2 of 1987. It was inherited into the first version of POSIX.1 and the Single Unix Specification. [2] The version of split bundled in GNU coreutils was written by Torbjorn Granlund and Richard Stallman. [3]
-k2,2n specifies sorting on the key starting and ending with column 2, and sorting numerically. If -k2 is used instead, the sort key would begin at column 2 and extend to the end of the line, spanning all the fields in between. -k1,1 dictates breaking ties using the value in column 1, sorting alphabetically by default. Note that bob, and chad ...
In Linux, if the script was executed by a regular user, the shell would attempt to execute the command rm -rf / as a regular user, and the command would fail. However, if the script was executed by the root user, then the command would likely succeed and the filesystem would be erased. It is recommended to use sudo on a per-command basis instead.
Comma-separated values (CSV) is a text file format that uses commas to separate values, and newlines to separate records. A CSV file stores tabular data (numbers and text) in plain text, where each line of the file typically represents one data record.
Command arguments are split in different ways across platforms. Some systems do not split up the arguments; for example, when running the script with the first line, #!/usr/bin/env python3 -c all text after the first space is treated as a single argument, that is, python3 -c will be passed as one argument to /usr/bin/env, rather than two arguments.
The Dataframe API was released as an abstraction on top of the RDD, followed by the Dataset API. In Spark 1.x, the RDD was the primary application programming interface (API), but as of Spark 2.x use of the Dataset API is encouraged [3] even though the RDD API is not deprecated. [4] [5] The RDD technology still underlies the Dataset API. [6] [7]