One method for sorting a file is to load the file into memory sort the data in memory then write the results. When the file cannot be loaded into memory due to resource limitations an external sort applicable. We will implement an external sort using replacement selection to establish initial runs followed by a polyphase merge sort to merge the runs into one sorted file. I highly recommend you consult Knuth [1998] as many details have been omitted.
For clarity I’ll assume that data is on one or more reels of magnetic tape. Figure 4-1 illustrates a 3-way polyphase merge. Initially in phase A all data is on tapes T1 and T2. Assume that the beginning of each tape is at the bottom of the frame. There are two sequential runs of data on T1: 4-8 and 6-7. Tape T2 has one run: 5-9. At phase B we’ve merged the first run from tapes T1 (4-8) and T2 (5-9) into a longer run on tape T3 (4-5-8-9). Phase C is simply renames the tapes so we may repeat the merge again. In phase D we repeat the merge with the final output on tape T3.
| Phase | T1 | T2 | T3 |
|---|---|---|---|
| A | 7 6 8 4 |
9 5 |
|
| B | 7 6 |
9 8 5 4 |
|
| C | 9 8 5 4 |
7 6 |
|
| D | 9 8 7 6 5 4 |
Several interesting details have been omitted from the previous illustration. For example how were the initial runs created? And did you notice that they merged perfectly with no extra runs on any tapes? Before I explain the method used for constructing initial runs let me digress for a bit.
In 1202 Leonardo Fibonacci presented the following exercise in his Liber Abbaci (Book of the Abacus): "How many pairs of rabbits can be produced from a single pair in a year’s time?" We may assume that each pair produces a new pair of offspring every month each pair becomes fertile at the age of one month and that rabbits never die. After one month there will be 2 pairs of rabbits; after two months there will be 3; the following month the original pair and the pair born during the first month will both usher in a new pair and there will be 5 in all; and so on. This series where each number is the sum of the two preceeding numbers is known as the Fibonacci sequence:
0 1 1 2 3 5 8 13 21 34 55 89 ... .
Curiously the Fibonacci series has found wide-spread application to everything from the arrangement of flowers on plants to studying the efficiency of Euclid’s algorithm. There’s even a Fibonacci Quarterly journal. And as you might suspect the Fibonacci series has something to do with establishing initial runs for external sorts.
Recall that we initially had one run on tape T2 and 2 runs on tape T1. Note that the numbers {1 2} are two sequential numbers in the Fibonacci series. After our first merge we had one run on T1 and one run on T2. Note that the numbers {1 1} are two sequential numbers in the Fibonacci series only one notch down. We could predict in fact that if we had 13 runs on T2 and 21 runs on T1 {13 21} we would be left with 8 runs on T1 and 13 runs on T3 {8 13} after one pass. Successive passes would result in run counts of {5 8} {3 5} {2 3} {1 1} and {0 1} for a total of 7 passes. This arrangement is ideal and will result in the minimum number of passes. Should data actually be on tape this is a big savings as tapes must be mounted and rewound for each pass. For more than 2 tapes higher-order Fibonacci numbers are used.
Initially all the data is on one tape. The tape is read and runs are distributed to other tapes in the system. After the initial runs are created they are merged as described above. One method we could use to create initial runs is to read a batch of records into memory sort the records and write them out. This process would continue until we had exhausted the input tape. An alternative algorithm replacement selection allows for longer runs. A buffer is allocated in memory to act as a holding place for several records. Initially the buffer is filled. Then the following steps are repeated until the input is exhausted:
Figure 4-2 illustrates replacement selection for a small file. To keep things simple I’ve allocated a 2-record buffer. Typically such a buffer would hold thousands of records. We load the buffer in step B and write the record with the smallest key (6) in step C. This is replaced with the next record (key 8). We select the smallest key >= 6 in step D. This is key 7. After writing key 7 we replace it with key 4. This process repeats until step F where our last key written was 8 and all keys are less than 8. At this point we terminate the run and start another.
| Step | Input | Buffer | Output |
|---|---|---|---|
| A | 5-3-4-8-6-7 | ||
| B | 5-3-4-8 | 6-7 | |
| C | 5-3-4 | 8-7 | 6 |
| D | 5-3 | 8-4 | 6-7 |
| E | 5 | 3-4 | 6-7-8 |
| F | 5-4 | 6-7-8 | 3 | |
| G | 5 | 6-7-8 | 3-4 | |
| H | 6-7-8 | 3-4-5 |
This strategy simply utilizes an intermediate buffer to hold values until the appropriate time for output. Using random numbers as input the average length of a run is twice the length of the buffer. However if the data is somewhat ordered runs can be extremely long. Thus this method is more effective than doing partial sorts.
When selecting the next output record we need to find the smallest key >= the last key written. One way to do this is to scan the entire list searching for the appropriate key. However when the buffer holds thousands of records execution time becomes prohibitive. An alternative method is to use a binary tree structure so that we only compare lg n items.
An ANSI-C implementation of an external sort is included. Function
makeRuns calls readRec to read the next record. Function readRec
employs the replacement selection algorithm (utilizing a binary tree) to fetch the next record
and makeRuns distributes the records in a Fibonacci distribution. If the number
of runs is not a perfect Fibonacci number
dummy runs are simulated at the beginning
of each file. Function mergeSort is then called to do a polyphase merge sort on
the runs.
Not implemented.