Databases
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    <p>Add a primary key which is auto incrementing and name it id.</p> <p>I wrote a script which takes all the words in <code>/etc/dict</code> and ran md5 over them, writing out their name and hash to create something like this:</p> <pre><code>"2af2fc92ed1ee8080d9ab015ab053074", "Windex's "bfa818f0cac66108daef757706e97a99", "Windhoek "88d0e322fb73a2e971bc982bd348c777", "Windows </code></pre> <p>My route of doing this was very hacky so I wont post my way of achieving it, but overall it was quite simple and just essentially was based around:</p> <pre><code>while read line do echo $line | md5sum | awk '{print $1}' done </code></pre> <p>So I created a database table:</p> <pre><code>CREATE TABLE whashes ( id int auto_increment primary key, hash varchar(32), word varchar(16) ); </code></pre> <p>And used:</p> <pre><code>INSERT INTO whashes (hash, word) VALUES </code></pre> <p>With the output of my script above. Running a test for speed.</p> <pre><code>SELECT * FROM `whashes` WHERE word LIKE "poop" LIMIT 0 , 30 </code></pre> <p>Runs in 0.0324 sec. This is with 100k words and should stay around that speed</p> <pre><code>SELECT * FROM `whashes` WHERE hash LIKE "b538baf8573b52b5bcfdd551fffa6e9d" LIMIT 0 , 30 </code></pre> <p>Runs in 0.0202 sec.</p> <p>From my understanding using an auto incrementing primary id integer key the computer is able keep a large amount of id's in cache and do somewhat of a binary search on those values. Without a key like this the database engine has to loop through each value checking it, compared to one check which reduces the amount needed to be checked by half each time. However, this explanation may be slightly incorrect however someone else may be able to explain further / correct me if I'm wrong. Just doing something as simple as this should give you a large improvement.</p>
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    1. POFinding HASH string in database (mysql and php)
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    1. USjett
    1. USjett
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      1. VTDownMod
    1. COHow would this speed up the process?
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      1. USDaryl Gill
    2. CO@DarylGill If your still curious I've tried to add a bit of background.
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      1. USjett
    3. CODid exactly as you said, and ran the sql search. 9minutes, for running all the records. This is a 9.1GB table.
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      1. USDexty
 

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