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That convention handles 80 percent of the tables we will encounter in our database, but there is always the other 20 percent to deal with Some tables serve a special purpose, such as join tables in many-to-many relationships You may decide that you need to set up a M:M relationship between a customer table and an address table If you think about it, this makes sense; a customer can have many addresses, and more than one customer can share an address As we discussed in 3, you need to create a third join table to set up this M:M relationship In this case, we start the table name with tbl_ and then we use both of the other table names in this new name In the example of customers and addresses, we would call the join table tbl_customer_address

#include <stdioh> #include <mathh> int main () { int i; int num_steps = 1000000; double x, pi, step, sum = 00; step = 10/(double) num_steps; for (i=0;i< num_steps; i++) { x = (i+05)*step; sum = sum + 40/(10+x*x); } pi = step * sum; printf("pi %lf\n",pi); return 0;

class CharCounter(TextFilter): @property def is_transformer(self): return False def __call__(self, text, chars): count = 0 for c in text: if c in chars: count += 1 return count

This text lter is not a transformer because rather than transforming the text it is given, it simply returns a count of the speci ed characters that occur in the text Here is an example of use:

vowel_counter = CharCounter() vowel_counter("dog fish and cat fish", "aeiou") # returns: 5

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Creating a parallel version of this program using the Loop Parallelism pattern is simple There is only one loop, so the inspection phase is trivial To make the loop iterations independent, we recognize that (1) the values of the variable x are local to each iteration, so this variable can be handled as a thread local or private variable and (2) the updates to sum define a reduction Reductions are supported by the OpenMP API Other than adding #include <omph>[2], only one additional line of code is needed to create a parallel version of the program The following is placed above the for loop:

Additionally, for lookup tables, some people like to add a prefix, such as lkup, after tbl_ This would give a table containing status codes a name like tbl_lkup_status_code Although we don t think this is a bad idea, it is not something we implement The main reason we avoid this strategy is that whoever ends being up the DBA for this database shouldn t care whether the table contains lookup data To the DBA it is just another table that the applications need to read, and possibly write to

Two other text lters are provided, both of which are transformers: RunLengthEncode and RunLengthDecode Here is how they are used:

rle_encoder = RunLengthEncode() rle_text = rle_encoder(text) rle_decoder = RunLengthDecode() original_text = rle_decoder(rle_text)

#pragma omp parallel for private(x) reduction(+:sum)

The run length encoder converts a string into UTF-8 encoded bytes, and replaces 0x00 bytes with the sequence 0x00, 0x01, 0x00, and any sequence of three to 255 repeated bytes with the sequence 0x00, count, byte If the string has lots of runs of four or more identical consecutive characters this can produce a shorter byte string than the raw UTF-8 encoded bytes The run length decoder takes a run length encoded byte string and returns the original string Here is the start of the RunLengthDecode class:

class RunLengthDecode(TextFilter): @property def is_transformer(self): return True def __call__(self, rle_bytes):

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