The New KornShell—ksh93
A conditional command in ksh93 evaluates a test-expression and returns either True or False. Conditional commands can be used as part of an “Or list” (||), “And list” (&&), or as part of an if-elif-else command. Conditional commands have the format:
[[ test-expression ]]
When used in conjunction with an “And list”, ksh93 evaluates the test-expression and will execute the “And component” only if the test-expression evaluates to True. We use a conditional command as part of an “And list” such that the return statement will be executed only if the test-expression is True.
[[ ${entries[0]} == $'*' ]] && return 2
The for command has two formats. The traditional format is provided to iterate on each word in a list. The format is:
for variableName [ in word-list ] do compound-list done
An arithmetic for command has been provided that is very similar to the C programming language for statement. The format is:
for (( initExpr ; condition ; loopExpr )) do compound-list done
The initExpression is evaluated by ksh prior to executing the for command. The condition is then evaluated prior to each iteration of compound-list. If the condition is non-zero, then ksh executes the compound-list. The loopExpression is evaluated at the end of each iteration.
A new typeset option has been added for name referencing. Using typeset -n nameReference=variableName will associate nameReference with variableName. A special alias, nameref, is provided as the equivalent for typeset -n. A shell script may use the reference name to refer to the variable name. Name referencing provides a convenient mechanism to pass the name of compound variables, or arrays, to ksh functions. This is more efficient than passing the variable's content.
In the lsc example, function setOutput must add the directory entries to the appropriate row and column. We could have defined separate functions named addToRow and addToColumn for this purpose. The main body of the functions, however, would be equivalent. Instead, we opted to write a single function addToCell that uses a nameref to the cell type passed as a parameter.
The addToCell function accepts three arguments, of which the first two are required. The first argument is the cell type and must be either row or col. We create a nameref using the local variable cell to be equivalent to the cell type specified. A reference to ${cell.index} would therefore be equivalent to ${row.index} or ${col.index}.
ksh functions are not inherited across invocations of ksh. A child shell process, for example, does not have access to the functions defined within the parent ksh invocation. This has historically limited the re-usability of ksh functions. As a solution, ksh93 will search the colon-separated list of directories given by the FPATH variable value, for an executable file with the same name as the function. In the lsc example, we can eliminate the last statement:
lsc "${@}"
The FPATH can then be set to the directory containing the lsc file. From the shell level, we can now call lsc. ksh93 will load the lsc script and will call the lsc function with the command line arguments specified. Note that the supporting functions defined in the lsc script are available to the lsc function.
A function autoload feature is provided, in which an auto-loaded function definition is loaded and retained within the ksh93 environment upon the first reference to the function name. This provides better performance since the search and load steps are eliminated for subsequent references.
Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
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Realizing the promise of Apache® Hadoop® requires the effective deployment of compute, memory, storage and networking to achieve optimal results. With its flexibility and multitude of options, it is easy to over or under provision the server infrastructure, resulting in poor performance and high TCO. Join us for an in depth, technical discussion with industry experts from leading Hadoop and server companies who will provide insights into the key considerations for designing and deploying an optimal Hadoop cluster.
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