SELECT * FROM Table1, Table2 WHERE Table1column1 = Table2column1 AND Table1column2 = Table2column2 in Java

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SELECT * FROM Table1, Table2 WHERE Table1column1 = Table2column1 AND Table1column2 = Table2column2
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In this case, it's not enough to ensure that column1 and column2 in the inner table are indexed Instead, you need to make a compound index on (column1, column2) in the inner table (GAIN: 7/8 if compound index rather than two separate indexes) It's also important to make sure that the joined columns in Table1 and Table2 have exactly the same data type and the same size (GAIN: 7/8 if the data types are exactly the same) That's not a trivial efficiency matter many DBMSs won't even use the index if there's a size mismatch What if the inner table is too big to fit in a cache and has no useful index Or what if there's a restrictive clause on the inner table too Well, then you're in trouble! The only bright spot in this situation is if you're using Microsoft or Sybase These DBMSs will internally "create temporary table which is clustered by the join key" then "populate temporary table by selecting the join columns and using the restrictive clause" Other DBMSs, more prosaically, simply make a temporary index on the inner table That might sound like a solution, but it's better to have a permanent index than a temporary index that gets created and dropped whenever the query comes along Another thing you can do if both tables are indexed is encourage the searches to occur in index order For example, suppose you have this query:
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SELECT * FROM Table1, Table2 WHERE Table1column1 = Table2column1
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For this example, assume that Table1column1 contains these values: {15, 35, 5, 7} If lookups of Table2column1 occur in that order, then the disk heads are jumping around But if you force the DBMS to search Table2 column1 in numeric order, that problem goes away To do this, change the query to:
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SELECT * FROM Table1, Table2
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WHERE Table1column1 = Table2column1 AND Table1column1 > 0 GAIN: 4/7
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WARNING Don't do this for Informix; it shows a loss The gain shown is for only seven DBMSs
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Remember that this works only if Table1column1 is indexed and the index is used by the DBMS The values found are now {5, 7, 15, 35}, and the lookups in the inner loop will be going forward in the index, which is good for caching and which makes read-aheads more useful A variation of this trick when the inner table is not indexed, is to encourage the searches to occur in ascending ROWID order This can be done if ROWIDs are accessible to the programmer, but a DBMS can also do this sort of thing automatically Here are our final three lessons about nested-loops: When your join contains an ANDed expression, make a compound index on the inner table's join columns
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Make sure that the joined columns in your inner table and outer table have exactly the same data type and the same size
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Search in index order
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The Bottom Line: Nested-Loop Join Plans
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The choice of inner/outer tables depends on restricting expressions, then index qualities, then table sizes You can influence the choice or you can go with the flow When conditions are good, nested-loops can produce result rows only two or three times more slowly than selections from a single unjoined table Nested-loops are the only strategy that works with weird conjunctions, such as LIKE joins Because they're flexible and easy to implement, nested-loop joins are supported by all DBMSs and are the default choice in most situations
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Typical OLTP queries will involve nested-loop joins 100% of the time, and even reporting queries will involve nested-loop joins more than 50% of the time
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IBM's Hybrid Join
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When it comes to tricks with ROWID order in the inner table, IBM is currently the most advanced DBMS Consider this SQL statement:
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SELECT * FROM Customer Outer, Invoice Inner WHERE Outercustomer_name = Innercustomer_name AND Outercustomer_name = 'SMITH'
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To resolve this query, IBM does the following:
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Sort data so outer table access will be in the order of the join column on the inner table When accessing the inner table, get RID (the IBM name for ROWID) and attach it to the row from the outer table This results in a temporary table with {outer table rows, inner table RID} Sort the temporary table by inner table RID
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The result is that IBM repeatedly scans the inner table but in order by inner table RID rather than rows This means there will be prefetches and quick access
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