Answer Posted / hari
Hash partitioning
method is the key
based partition
method... And lookup
wich also compare and
retrieve the data
based on key
column... So by using
hash method wil
increase performance
in lookup...
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create a job that splits the data in the Jobs.txt file into
four output files. You will direct the data to the
different output files using constraints. • Job name:
JobLevels
• Source file: Jobs.txt
• Target file 1: LowLevelJobs.txt
− min_lvl between 0 and 25 inclusive.
− Same column types and headings as Jobs.txt.
− Include column names in the first line of the output file.
− Job description column should be preceded by the
string “Job
Title:” and embedded within square brackets. For example, if
the job description is “Designer”, the derived value
is: “Job
Title: [Designer]”.
• Target file 2: MidLevelJobs.txt
− min_lvl between 26 and 100 inclusive.
− Same format and derivations as Target file 1.
• Target file 3: HighLevelJobs.txt
− min_lvl between 101 and 500 inclusive.
− Same format and derivations as Target file 1.
• Rejects file: JobRejects.txt
− min_lvl is out of range, i.e., below 0 or above 500.
− This file has only two columns: job_id and reject_desc.
− reject_desc is a variable-length text field, maximum
length
100. It should contain a string of the form: “Level out of
range:
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