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    1. COFrom my research, what I understood is that if you have 1000 records in a file and you read 100 at a time, sort that 100 and put the sorted version in a temp file which will create 10 temp sorted files. Then read two files sequentially and create another sorted (larger now) file and delete the other two which just have been read. Continue until you have one file. SERIOUSLY? Now, say you have 10 million records in a file and you read 5000 at a time, how many temp you created and how much time it's gonna cost you to get the final version?
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    2. COAn external sort is always slower compared to an in-memory sorty, but you are no longer limited by your ram. if speed is important to you and you have several machines at hand, take a look at hadoop (mentioned in other replies). It does an external sort where all individual sort operations can happen on many machines in parallel.
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    3. COErika: When you merge the (sorted, smaller) files, you can have more than two open, it's just slightly more straightforward describing the algorithm using just two temp files. But, if you need a file taht's larger than the available memory sorted, you'll have to (eventually) do it that way anyway and the merging operation is (relatively) fast, as all it needs to do is keep N file pointers open and find the lowest of N "next record"s to know what to emit next. I guess the critical piece of tuning is choosing how many records to keep in each temporary file.
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Guidance
A row detail

Detail views are divided into sections. All the information in the data section comes from columns in the selected row. The other sections display data from other, related rows.

Related data can be related in a to-one or a to-many fashion. Captions of data related in a to-many fashion link to a list view showing a filtered view of the table.

Try moving around until you find a non-empty to-many entry and click on the label to get to one. You can move back to the root by clicking on the database name in the header.

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