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Overview
Comment: | documentation updates (CVS 112) |
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Downloads: | Tarball | ZIP archive |
Timelines: | family | ancestors | descendants | both | trunk |
Files: | files | file ages | folders |
SHA1: |
c686c6076abadcb715fe74436fa8bab4 |
User & Date: | drh 2000-07-30 20:04:43.000 |
Context
2000-07-31
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11:57 | fix a configuration problem on TAC-4 (CVS 113) (check-in: 69b73ea3a0 user: drh tags: trunk) | |
2000-07-30
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20:04 | documentation updates (CVS 112) (check-in: c686c6076a user: drh tags: trunk) | |
2000-07-29
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13:20 | better column names in the shell (CVS 111) (check-in: 57022a9d50 user: drh tags: trunk) | |
Changes
Changes to src/vdbe.c.
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37 38 39 40 41 42 43 | ** inplicit conversion from one type to the other occurs as necessary. ** ** Most of the code in this file is taken up by the sqliteVdbeExec() ** function which does the work of interpreting a VDBE program. ** But other routines are also provided to help in building up ** a program instruction by instruction. ** | | | 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 | ** inplicit conversion from one type to the other occurs as necessary. ** ** Most of the code in this file is taken up by the sqliteVdbeExec() ** function which does the work of interpreting a VDBE program. ** But other routines are also provided to help in building up ** a program instruction by instruction. ** ** $Id: vdbe.c,v 1.37 2000/07/30 20:04:43 drh Exp $ */ #include "sqliteInt.h" #include <unistd.h> /* ** SQL is translated into a sequence of instructions to be ** executed by a virtual machine. Each instruction is an instance |
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1966 1967 1968 1969 1970 1971 1972 | PopStack(p, 1); break; } /* Opcode: KeyAsData P1 P2 * ** ** Turn the key-as-data mode for cursor P1 either on (if P2==1) or | | | 1966 1967 1968 1969 1970 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 | PopStack(p, 1); break; } /* Opcode: KeyAsData P1 P2 * ** ** Turn the key-as-data mode for cursor P1 either on (if P2==1) or ** off (if P2==0). In key-as-data mode, the OP_Field opcode pulls ** data off of the key rather than the data. This is useful for ** processing compound selects. */ case OP_KeyAsData: { int i = pOp->p1; if( i>=0 && i<p->nCursor && p->aCsr[i].pCursor!=0 ){ p->aCsr[i].keyAsData = pOp->p2; |
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Changes to www/opcode.tcl.
1 2 3 | # # Run this Tcl script to generate the sqlite.html file. # | | | 1 2 3 4 5 6 7 8 9 10 11 | # # Run this Tcl script to generate the sqlite.html file. # set rcsid {$Id: opcode.tcl,v 1.4 2000/07/30 20:04:43 drh Exp $} puts {<html> <head> <title>SQLite Virtual Machine Opcodes</title> </head> <body bgcolor=white> <h1 align=center> |
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51 52 53 54 55 56 57 | <p>In order to execute an SQL statement, the SQLite library first parses the SQL, analyzes the statement, then generates a short program to execute the statement. The program is generated for a "virtual machine" implemented by the SQLite library. This document describes the operation of that virtual machine.</p> <p>This document is intended as a reference, not a tutorial. | | | | 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 | <p>In order to execute an SQL statement, the SQLite library first parses the SQL, analyzes the statement, then generates a short program to execute the statement. The program is generated for a "virtual machine" implemented by the SQLite library. This document describes the operation of that virtual machine.</p> <p>This document is intended as a reference, not a tutorial. A separate <a href="vdbe.html">Virtual Machine Tutorial</a> is available. If you are looking for a narrative description of how the virtual machine works, you should read the tutorial and not this document. Once you have a basic idea of what the virtual machine does, you can refer back to this document for the details on a particular opcode.</p> <p>The source code to the virtual machine is in the <b>vdbe.c</b> source file. All of the opcode definitions further down in this document are |
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Changes to www/vdbe.tcl.
1 2 3 | # # Run this Tcl script to generate the vdbe.html file. # | | > | | | | < > | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 | # # Run this Tcl script to generate the vdbe.html file. # set rcsid {$Id: vdbe.tcl,v 1.5 2000/07/30 20:04:43 drh Exp $} puts {<html> <head> <title>The Virtual Database Engine of SQLite</title> </head> <body bgcolor=white> <h1 align=center> The Virtual Database Engine of SQLite </h1>} puts "<p align=center> (This page was last modified on [lrange $rcsid 3 4] GMT) </p>" # puts { # <blockquote><font color="red"><b>This document is # currently under development. It is incomplete and contains # errors. Use it accordingly.</b></font></blockquote> # } puts { <p>If you want to know how the SQLite library works internally, you need to begin with a solid understanding of the Virtual Database Engine or VDBE. The VDBE occurs right in the middle of the processing stream (see the <a href="arch.html">architecture diagram</a>) and so it seems to touch most parts of the library. Even |
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92 93 94 95 96 97 98 99 100 101 102 103 104 105 | <blockquote><pre> INSERT INTO examp VALUES('Hello, World!',99); </pre></blockquote> <p>We can see the VDBE program that SQLite uses to implement this INSERT using the <b>sqlite</b> command-line utility. First start up <b>sqlite</b> on a new, empty database, then create the table. Finally, enter the INSERT statement shown above, but precede the INSERT with the special keyword "EXPLAIN". The EXPLAIN keyword will cause <b>sqlite</b> to print the VDBE program rather than execute it. We have:</p> } proc Code {body} { | > > > | 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 | <blockquote><pre> INSERT INTO examp VALUES('Hello, World!',99); </pre></blockquote> <p>We can see the VDBE program that SQLite uses to implement this INSERT using the <b>sqlite</b> command-line utility. First start up <b>sqlite</b> on a new, empty database, then create the table. Next change the output format of <b>sqlite</b> to a form that is designed to work with VDBE program dumps by entering the ".explain" command. Finally, enter the INSERT statement shown above, but precede the INSERT with the special keyword "EXPLAIN". The EXPLAIN keyword will cause <b>sqlite</b> to print the VDBE program rather than execute it. We have:</p> } proc Code {body} { |
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149 150 151 152 153 154 155 | opened cursors must be opened with the same P2 value. It is not allowed to have one cursor open for reading a file and another cursor open for writing that same file.</p> <p>The second instruction, New, generates an integer key that has not been previously used in the file "examp". The New instruction uses its P1 operand as the handle of a cursor for the file | | | 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 | opened cursors must be opened with the same P2 value. It is not allowed to have one cursor open for reading a file and another cursor open for writing that same file.</p> <p>The second instruction, New, generates an integer key that has not been previously used in the file "examp". The New instruction uses its P1 operand as the handle of a cursor for the file for which the new key will be generated. The generated key is pushed onto the stack. The P2 and P3 operands are not used by the New instruction.</p> <p>The third instruction, String, simply pushes its P3 operand onto the stack. After the string instruction executes, the stack will contain two elements, as follows:</p> } |
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193 194 195 196 197 198 199 | the stack looks like this:</p> } stack {A data record holding "Hello, World!" and 99} \ {A random integer key} puts {<p>The last instruction pops the top two elements from the stack | | | 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 | the stack looks like this:</p> } stack {A data record holding "Hello, World!" and 99} \ {A random integer key} puts {<p>The last instruction pops the top two elements from the stack and uses them as data and key to make a new entry in the database file pointed to by cursor P1. This instruction is where the insert actually occurs.</p> <p>After the last instruction executes, the program counter advances to one past the last instruction, which causes the VDBE to halt. When the VDBE halts, it automatically closes all open cursors, frees any elements left on the stack, |
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297 298 299 300 301 302 303 | prototype:</p> <blockquote><pre> int Callback(void *pUserData, int nColumn, char *azData[], char *azColumnName[]); </pre></blockquote> <p>The SQLite library supplies the VDBE with a pointer to the callback function | > > | | 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 | prototype:</p> <blockquote><pre> int Callback(void *pUserData, int nColumn, char *azData[], char *azColumnName[]); </pre></blockquote> <p>The SQLite library supplies the VDBE with a pointer to the callback function and the <b>pUserData</b> pointer. (Both the callback and the user data were originally passed in as argument to the <b>sqlite_exec()</b> API function.) The job of the VDBE is to come up with values for <b>nColumn</b>, <b>azData[]</b>, and <b>azColumnName[]</b>. <b>nColumn</b> is the number of columns in the results, of course. <b>azColumnName[]</b> is an array of strings where each string is the name of one of the result column. <b>azData[]</b> is an array of strings holding the actual data.</p> |
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751 752 753 754 755 756 757 | columns from all entries of the sqlite_master table. The "sql" column contains the complete SQL text of the CREATE statement that originally generated the index or table. This text is fed back into the SQLite parser and used to reconstruct the internal data structures describing the index or table.</p> | | | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > | > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > 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The "sql" column contains the complete SQL text of the CREATE statement that originally generated the index or table. This text is fed back into the SQLite parser and used to reconstruct the internal data structures describing the index or table.</p> <h2>Using Indexes To Speed Searching</h2> <p>In the example queries above, every row of the table being queried must be loaded off of the disk and examined, even if only a small percentage of the rows end up in the result. This can take a long time on a big table. To speed things up, SQLite can use an index.</p> <p>An GDBM file associates a key with some data. For a SQLite table, the GDBM file is set up so that the key is a integer and the data is the information for one row of the table. Indices in SQLite reverse this arrangement. The GDBM key is (some of) the information being stored and the GDBM data is an integer. To access a table row that has some particular content, we first look up the content in the GDBM index file to find its integer index, then we use that integer to look up the complete record in the GDBM table file.</p> <p>Note that because GDBM uses hashing instead of b-trees, indices are only helpful when the WHERE clause of the SELECT statement contains tests for equality. Inequalities will not work since there is no way to ask GDBM to fetch records that do not match a key. So, in other words, queries like the following will use an index if it is available:</p> <blockquote><pre> SELECT * FROM examp WHERE two==50; </pre></blockquote> <p>If there exists an index that maps the "two" column of the "examp" table into integers, then SQLite will use that index to find the integer keys of all rows in examp that have a value of 50 for column two. But the following query will not use an index:</p> <blockquote><pre> SELECT * FROM examp WHERE two<50; </pre></blockquote> <p>GDBM does not have the ability to select records based on a magnitude comparison, and so there is no way to use an index to speed the search in this case.</p> <p>To understand better how indices work, lets first look at how they are created. Let's go ahead and put an index on the two column of the examp table. We have:</p> <blockquote><pre> CREATE INDEX examp_idx1 ON examp(two); </pre></blockquote> <p>The VDBE code generated by the above statement looks like the following:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 Open 0 0 examp 1 Open 1 1 examp_idx1 2 Open 2 1 sqlite_master 3 New 2 0 4 String 0 0 index 5 String 0 0 examp_idx1 6 String 0 0 examp 7 String 0 0 CREATE INDEX examp_idx1 ON examp(two) 8 MakeRecord 4 0 9 Put 2 0 10 Close 2 0 11 Next 0 17 12 Key 0 0 13 Field 0 1 14 MakeKey 1 0 15 PutIdx 1 0 16 Goto 0 11 17 Noop 0 0 18 Close 1 0 19 Close 0 0 } puts { <p>Remember that every table (except sqlite_master) and every named index has an entry in the sqlite_master table. Since we are creating a new index, we have to add a new entry to sqlite_master. This is handled by instructions 2 through 10. Adding an entry to sqlite_master works just like any other INSERT statement so we will not say anymore about it here. In this example, we want to focus on populating the new index with valid data, which happens on instructions 0 and 1 and on instructions 11 through 19.</p> <p>The first thing that happens is that we open the table being indexed for reading. In order to construct an index for a table, we have to know what is in that table. The second instruction opens the index file for writing.</p> <p>Instructions 11 through 16 implement a loop over every row of the table being indexed. For each table row, we first extract the integer key for that row in instruction 12, then get the value of the two column in instruction 13. The MakeKey instruction at 14 converts data from the two column (which is on the top of the stack) into a valid index key. For an index on a single column, this is basically a no-op. But if the P1 operand to MakeKey had been greater than one multiple entries would have been popped from the stack and converted into a single index key. The PutIdx instruction at 15 is what actually creates the index entry. PutIdx pops two elements from the stack. The top of the stack is used as a key to fetch an entry from the GDBM index file. Then the integer which was second on stack is added to the set of integers for that index and the new record is written back to the GDBM file. Note that the same index entry can store multiple integers if there are two or more table entries with the same value for the two column. </p> <p>Now let's look at how this index will be used. Consider the following query:</p> <blockquote><pre> SELECT * FROM examp WHERE two==50; </pre></blockquote> <p>SQLite generates the following VDBE code to handle this query:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 ColumnCount 2 0 1 ColumnName 0 0 one 2 ColumnName 1 0 two 3 Open 0 0 examp 4 Open 1 0 examp_idx1 5 Integer 50 0 6 MakeKey 1 0 7 Fetch 1 0 8 NextIdx 1 14 9 Fetch 0 0 10 Field 0 0 11 Field 0 1 12 Callback 2 0 13 Goto 0 8 14 Close 0 0 15 Close 1 0 } puts { <p>The SELECT begins in a familiar fashion. First the column names are initialized and the table being queried is opened. Things become different beginning with instruction 4 where the index file is also opened. Instructions 5 and 6 make a key with the value of 50 and instruction 7 fetches the record of the GDBM index file that has this key. This will be the only fetch from the index file.</p> <p>Instructions 8 through 13 implement a loop over all integers in the payload of the index record that was fetched by instruction 7. The NextIdx operation works much like the Next and ListRead operations that are discussed above. Each NextIdx instruction reads a single integer from the payload of the index record and falls through, except that if there are no more records it jumps immediately to 14.</p> <p>The Fetch instruction at 9 loads a single record from the GDBM file that holds the table. Then there are two Field instructions to construct the result and the callback is invoked. All this is the same as we have seen before. The only difference is that the loop is now constructed using NextIdx instead of Next.</p> <p>Since the index is used to look up values in the table, it is important that the index and table be kept consistent. Now that there is an index on the examp table, we will have to update that index whenever data is inserted, deleted, or changed in the examp table. Remember the first example above how we were able to insert a new row into the examp table using only 6 VDBE instructions. Now that this table is indexed, 10 instructions are required. The SQL statement is this:</p> <blockquote><pre> INSERT INTO examp VALUES('Hello, World!',99); </pre></blockquote> <p>And the generated code looks like this:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 Open 0 1 examp 1 Open 1 1 examp_idx1 2 New 0 0 3 Dup 0 0 4 String 0 0 Hello, World! 5 Integer 99 0 6 MakeRecord 2 0 7 Put 0 0 8 Integer 99 0 9 MakeKey 1 0 10 PutIdx 1 0 } puts { <p>At this point, you should understand the VDBE well enough to figure out on your own how the above program works. So we will not discuss it further in this text.</p> <h2>Joins</h2> <p>In a join, two or more tables are combined to generate a single result. The result table consists of every possible combination of rows from the tables being joined. The easiest and most natural way to implement this is with nested loops.</p> <p>Recall the query template discussed above where there was a single loop that searched through every record of the table. In a join we have basically the same thing except that there are nested loops. For example, to join two tables, the query template might look something like this:</p> <p> <ol> <li>Initialize the <b>azColumnName[]</b> array for the callback.</li> <li>Open two cursors, one to each of the two tables being queried.</li> <li>For each record in the first table, do: <ol type="a"> <li>For each record in the second table do: <ol type="i"> <li>If the WHERE clause evaluates to FALSE, then skip the steps that follow and continue to the next record.</li> <li>Compute all columns for the current row of the result.</li> <li>Invoke the callback function for the current row of the result.</li> </ol></li> </ol> <li>Close both cursors.</li> </ol> </p> <p>This template will work, but it is likely to be slow since we are now dealing with an O(N<sup>2</sup>) loop. But it often works out that the WHERE clause can be factored into terms and that one or more of those terms will involve only columns in the first table. When this happens, we can factor part of the WHERE clause test out of the inner loop and gain a lot of efficiency. So a better template would be something like this:</p> <p> <ol> <li>Initialize the <b>azColumnName[]</b> array for the callback.</li> <li>Open two cursors, one to each of the two tables being queried.</li> <li>For each record in the first table, do: <ol type="a"> <li>Evaluate terms of the WHERE clause that only involve columns from the first table. If any term is false (meaning that the whole WHERE clause must be false) then skip the rest of this loop and continue to the next record.</li> <li>For each record in the second table do: <ol type="i"> <li>If the WHERE clause evaluates to FALSE, then skip the steps that follow and continue to the next record.</li> <li>Compute all columns for the current row of the result.</li> <li>Invoke the callback function for the current row of the result.</li> </ol></li> </ol> <li>Close both cursors.</li> </ol> </p> <p>Additional speed-up can occur if an index can be used to speed the search of either or the two loops.</p> <p>SQLite always constructs the loops in the same order as the tables appear in the FROM clause of the SELECT statement. The left-most table becomes the outer loop and the right-most table becomes the inner loop. It is possible, in theory, to reorder the loops in some circumstances to speed the evaluation of the join. But SQLite does not attempt this optimization.</p> <p>You can see how SQLite constructs nested loops in the following example:</p> <blockquote><pre> CREATE TABLE examp2(three int, four int); SELECT * FROM examp, examp2 WHERE two<50 AND four==two; </pre></blockquote> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 ColumnCount 4 0 1 ColumnName 0 0 examp.one 2 ColumnName 1 0 examp.two 3 ColumnName 2 0 examp2.three 4 ColumnName 3 0 examp2.four 5 Open 0 0 examp 6 Open 1 0 examp2 7 Next 0 21 8 Field 0 1 9 Integer 50 0 10 Ge 0 7 11 Next 1 7 12 Field 1 1 13 Field 0 1 14 Ne 0 11 15 Field 0 0 16 Field 0 1 17 Field 1 0 18 Field 1 1 19 Callback 4 0 20 Goto 0 11 21 Close 0 0 22 Close 1 0 } puts { <p>The outer loop over table examp is implement by instructions 7 through 20. The inner loop is instructions 11 through 20. Notice that the "two<50" term of the WHERE expression involves only columns from the first table and can be factored out of the inner loop. SQLite does this and implements the "two<50" test in instructions 8 through 10. The "four==two" test is implement by instructions 12 through 14 in the inner loop.</p> <p>SQLite does not impose any arbitrary limits on the tables in a join. It also allows a table to be joined with itself.</p> <h2>The ORDER BY clause</h2> <p>As noted previously, GDBM does not have any facility for handling inequalities. A consequence of this is that we cannot sort on disk using GDBM. All sorted must be done in memory.</p> <p>SQLite implements the ORDER BY clause using a special set of instruction control an object called a sorter. In the inner-most loop of the query, where there would normally be a Callback instruction, instead a record is constructed that contains both callback parameters and a key. This record is added to a linked list. After the query loop finishes, the list of records is sort and this walked. For each record on the list, the callback is invoked. Finally, the sorter is closed and memory is deallocated.</p> <p>We can see the process in action in the following query:</p> <blockquote><pre> SELECT * FROM examp ORDER BY one DESC, two; </pre></blockquote> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 SortOpen 0 0 1 ColumnCount 2 0 2 ColumnName 0 0 one 3 ColumnName 1 0 two 4 Open 0 0 examp 5 Next 0 14 6 Field 0 0 7 Field 0 1 8 SortMakeRec 2 0 9 Field 0 0 10 Field 0 1 11 SortMakeKey 2 0 -+ 12 SortPut 0 0 13 Goto 0 5 14 Close 0 0 15 Sort 0 0 16 SortNext 0 19 17 SortCallback 2 0 18 Goto 0 16 19 SortClose 0 0 } puts { <p>The sorter is opened on the first instruction. The VDBE allows any number of sorters, but in practice no more than one is every used.</p> <p>The query loop is built from instructions 5 through 13. Instructions 6 through 8 build a record that contains the azData[] values for a single invocation of the callback. A sort key is generated by instructions 9 through 11. Instruction 12 combines the invocation record and the sort key into a single entry and puts that entry on the sort list.<p> <p>The P3 argument of instruction 11 is of particular interest. The sort key is formed by prepending one character from P3 to each string and concatenating all the strings. The sort comparison function will look at this character to determine whether the sort order is ascending or descending. In this example, the first column should be sorted in descending order so its prefix is "-" and the second column should sort in ascending order so its prefix is "+".</p> <p>After the query loop ends, the table being queried is closed at instruction 14. This is done early in order to allow other processes or threads to access that table, if desired. The list of records that was built up inside the query loop is sorted by the instruction at 15. Instructions 16 through 18 walk through the record list (which is now in sorted order) and invoke the callback once for each record. Finally, the sorter is closed at instruction 19.</p> <h2>Aggregate Functions And The GROUP BY and HAVING Clauses</h2> <p>To compute aggregate functions, the VDBE implements a special data structure and instructions for controlling that data structure. The data structure is an unordered set of buckets, where each bucket has a key and one or more memory locations. Within the query loop, the GROUP BY clause is used to construct a key and the bucket with that key is brought into focus. A new bucket is created with the key if one did not previously exist. Once the bucket is in focus, the memory locations of the bucket are used to accumulate the values of the various aggregate functions. After the query loop terminates, the each bucket is visited once to generate a single row of the results.</p> <p>An example will help to clarify this concept. Consider the following query:</p> <blockquote><pre> SELECT three, min(three+four)+avg(four) FROM examp2 GROUP BY three; </pre></blockquote> } puts { <p>The VDBE code generated for this query is as follows:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 ColumnCount 2 0 1 ColumnName 0 0 three 2 ColumnName 1 0 min(three+four)+avg(four) 3 AggReset 0 4 4 Open 0 0 examp2 5 Next 0 23 6 Field 0 0 7 MakeKey 1 0 8 AggFocus 0 11 9 Field 0 0 10 AggSet 0 0 11 Field 0 0 12 Field 0 1 13 Add 0 0 14 AggGet 0 1 15 Min 0 0 16 AggSet 0 1 17 AggIncr 1 2 18 Field 0 1 19 AggGet 0 3 20 Add 0 0 21 AggSet 0 3 22 Goto 0 5 23 Close 0 0 24 AggNext 0 33 25 AggGet 0 0 26 AggGet 0 1 27 AggGet 0 3 28 AggGet 0 2 29 Divide 0 0 30 Add 0 0 31 Callback 2 0 32 Goto 0 24 33 Noop 0 0 } puts { <p>The first instruction of interest is the AggReset at 3. The AggReset instruction initializes the set of buckets to be the empty set and specifies the number of memory slots available in each bucket. In this example, each bucket will hold four memory slots. It is not obvious, but if you look closely at the rest of the program you can figure out what each of these four slots is intended for.</p> <blockquote><table border="2" cellpadding="5"> <tr><th>Memory Slot</th><th>Intended Use Of This Memory Slot</th></tr> <tr><td>0</td><td>The "three" column -- the key to the bucket</td></tr> <tr><td>1</td><td>The minimum "three+four" value</td></tr> <tr><td>2</td><td>The number of records with the same key. This value divides the value in slot 3 to compute "avg(four)".</td></tr> <tr><td>3</td><td>The sum of all "four" values. This is used to compute "avg(four)".</td></tr> </table></blockquote> <p>The query loop is implement by instructions 5 through 22. The aggregate key specified by the GROUP BY clause is computed by instructions 6 and 7. Instruction 8 causes the appropriate bucket to come into focus. If a bucket with the given key does not already exists, a new bucket is created and control falls through to instructions 9 and 10 which initialize the bucket. If the bucket does already exist, then a jump is made to instruction 11. The values of aggregate functions are updated by the instructions between 11 and 21. Instructions 11 through 16 update memory slot 1 to hold the next value "min(three+four)". The counter in slot 2 is incremented by instruction 17. Finally the sum of the "four" column is updated by instructions 18 through 21.</p> <p>After the query loop is finished, the GDBM table is closed at instruction 23 so that its lock will be released and it can be used by other threads or processes. The next step is to loop over all aggregate buckets and output one row of the result for each bucket. This is done by the loop at instructions 24 through 32. The AggNext instruction at 24 brings the next bucket into focus, or jumps to the end of the loop if all buckets have been examined already. The first column of the result ("three") is computed by instruction 25. The second result column ("min(three+four)+avg(four)") is computed by instructions 26 through 30. Notice how the avg() function is computed as if it where sum()/count(). Finally, the callback is invoked at instruction 31.</p> <p>In summary then, any query with aggregate functions is implemented by two loops. The first loop scans the input table and computes aggregate information into buckets and the second loop scans through all the buckets to compute the final result.</p> <p>The realization that an aggregate query is really two consequtive loops makes it much easier to understand the difference between a WHERE clause and a HAVING clause in SQL query statement. The WHERE clause is a restriction on the first loop and the HAVING clause is a restriction on the second loop. You can see this by adding both a WHERE and a HAVING clause to our example query:</p> <blockquote><pre> SELECT three, min(three+four)+avg(four) FROM examp2 WHERE three>four GROUP BY three HAVING avg(four)<10; </pre></blockquote> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 ColumnCount 2 0 1 ColumnName 0 0 three 2 ColumnName 1 0 min(three+four)+avg(four) 3 AggReset 0 4 4 Open 0 0 examp2 5 Next 0 26 6 Field 0 0 7 Field 0 1 8 Le 0 5 9 Field 0 0 10 MakeKey 1 0 11 AggFocus 0 14 12 Field 0 0 13 AggSet 0 0 14 Field 0 0 15 Field 0 1 16 Add 0 0 17 AggGet 0 1 18 Min 0 0 19 AggSet 0 1 20 AggIncr 1 2 21 Field 0 1 22 AggGet 0 3 23 Add 0 0 24 AggSet 0 3 25 Goto 0 5 26 Close 0 0 27 AggNext 0 41 28 AggGet 0 3 29 AggGet 0 2 30 Divide 0 0 31 Integer 10 0 32 Ge 0 27 33 AggGet 0 0 34 AggGet 0 1 35 AggGet 0 3 36 AggGet 0 2 37 Divide 0 0 38 Add 0 0 39 Callback 2 0 40 Goto 0 27 41 Noop 0 0 } puts { <p>The code generated in this last example is the same as the previous except for the addition of two conditional jumps used to implement the extra WHERE and HAVING clauses. The WHERE clause is implemented by instructions 6 through 8 in the query loop. The HAVING clause is implemented by instruction 28 through 32 in the output loop.</p> <h2>Using SELECT Statements As Terms In An Expression</h2> <p>The very name "Structured Query Language" tells us that SQL should support nested queries. And, in fact, two different kinds of nesting are supported. Any SELECT statement that returns a single-row, single-column result can be used as a term in an expression of another SELECT statement. And, a SELECT statement that returns a single-column, multi-row result can be used as the right-hand operand of the IN and NOT IN operators. We will begin this section with an example of the first kind of nesting, where a single-row, single-column SELECT is used as a term in an expression of another SELECT. Here is our example:</p> <blockquote><pre> SELECT * FROM examp WHERE two!=(SELECT three FROM examp2 WHERE four=5); </pre></blockquote> <p>The way SQLite deals with this is to first run the inner SELECT (the one against examp2) and store its result in a private memory cell. SQLite then substitutes the value of this private memory cell for the inner SELECT when it evaluations the outer SELECT. The code looks like this:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 Null 0 0 1 MemStore 0 0 2 Open 0 0 examp2 3 Next 0 11 4 Field 0 1 5 Integer 5 0 6 Ne 0 3 7 Field 0 0 8 MemStore 0 0 9 Goto 0 11 10 Goto 0 3 11 Close 0 0 12 ColumnCount 2 0 13 ColumnName 0 0 one 14 ColumnName 1 0 two 15 Open 0 0 examp 16 Next 0 24 17 Field 0 1 18 MemLoad 0 0 19 Eq 0 16 20 Field 0 0 21 Field 0 1 22 Callback 2 0 23 Goto 0 16 24 Close 0 0 } puts { <p>The private memory cell is initialized to NULL by the first two instructions. Instructions 2 through 11 implement the inner SELECT statement against the examp2 table. Notice that instead of sending the result to a callback or storing the result on a sorter, the result of the query is pushed into the memory cell by instruction 8 and the loop is abandoned by the jump at instruction 9. The jump at instruction at 10 is vestigial and never executes.</p> <p>The outer SELECT is implemented by instructions 12 through 24. In particular, the WHERE clause that contains the nested select is implemented by instructions 17 through 19. You can see that the result of the inner select is loaded onto the stack by instruction 18 and used by the conditional jump at 19.</p> <p>When the result of a sub-select is a scalar, a single private memory cell can be used, as shown in the previous example. But when the result of a sub-select is a vector, such as when the sub-select is the right-hand operand of IN or NOT IN, a different approach is needed. In this case, the result of the sub-select is stored in a temporary GDBM table and the contents of that table are tested using the Found or NotFound operators. Consider this example:</p> <blockquote><pre> SELECT * FROM examp WHERE two IN (SELECT three FROM examp2); </pre></blockquote> <p>The code generated to implement this last query is as follows:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 Open 0 1 1 Open 1 0 examp2 2 Next 1 7 3 Field 1 0 4 String 0 0 5 Put 0 0 6 Goto 0 2 7 Close 1 0 8 ColumnCount 2 0 9 ColumnName 0 0 one 10 ColumnName 1 0 two 11 Open 1 0 examp 12 Next 1 19 13 Field 1 1 14 NotFound 0 12 15 Field 1 0 16 Field 1 1 17 Callback 2 0 18 Goto 0 12 19 Close 1 0 } puts { <p>The temporary table in which the results of the inner SELECT are stored is created by instruction 0. Notice that the P3 field of this Open instruction is empty. An empty P3 field on an Open instruction tells the VDBE to create a temporary table. This temporary table will be automatically deleted from the disk when the VDBE halts.</p> <p>The inner SELECT statement is implemented by instructions 1 through 7. All this code does is make an entry in the temporary table for each row of the examp2 table. The key for each temporary table entry is the "three" column of examp2 and the data entries is an empty string since it is never used.</p> <p>The outer SELECT is implemented by instructions 8 through 19. In particular, the WHERE clause containing the IN operator is implemented by two instructions at 13 and 14. Instruction 13 pushes the value of the "two" column for the current row onto the stack and instruction 14 tests to see if top of the stack matches any key in the temporary table. All the rest of the code is the same as what has been shown before.</p> <h2>Compound SELECT Statements</h2> <p>SQLite also allows two or more SELECT statements to be joined as peers using operators UNION, UNION ALL, INTERSECT, and EXCEPT. These compound select statements are implemented using temporary tables. The implementation is slightly different for each operator, but the basic ideas are the same. For an example we will use the EXCEPT operator.</p> <blockquote><pre> SELECT two FROM examp EXCEPT SELECT four FROM examp2; </pre></blockquote> <p>The result of this last example should be every unique value of the two column in the examp table except any value that is in the four column of examp2 is removed. The code to implement this query is as follows:</p> } Code { addr opcode p1 p2 p3 ---- ------------ ----- ----- ---------------------------------------- 0 Open 0 1 1 KeyAsData 0 1 2 Open 1 0 examp 3 Next 1 9 4 Field 1 1 5 MakeRecord 1 0 6 String 0 0 7 Put 0 0 8 Goto 0 3 9 Close 1 0 10 Open 1 0 examp2 11 Next 1 16 12 Field 1 1 13 MakeRecord 1 0 14 Delete 0 0 15 Goto 0 11 16 Close 1 0 17 ColumnCount 1 0 18 ColumnName 0 0 four 19 Next 0 23 20 Field 0 0 21 Callback 1 0 22 Goto 0 19 23 Close 0 0 } puts { <p>The temporary table in which the result is built is created by instruction 0. Three loops then follow. The loop at instructions 3 through 8 implements the first SELECT statement. The second SELECT statement is implemented by the loop at instructions 11 through 15. Finally, a loop at instructions 19 through 22 reads the temporary table and invokes the callback once for each row in the result.</p> <p>Instruction 1 is of particular importance in this example. Normally, the Field opcode extracts the value of a column from a larger record in the data of a GDBM file entry. Instructions 1 sets a flag on the temporary table so that Field will instead treat the key of the GDBM file entry as if it were data and extract column information from the key.</p> <p>Here is what is going to happen: The first SELECT statement will construct rows of the result and save each row as the key of an entry in the temporary table. The data for each entry in the temporary table is a never used so we fill it in with an empty string. The second SELECT statement also constructs rows, but the rows constructed by the second SELECT are removed from the temporary table. That is why we want the rows to be stored in the key of the GDBM file instead of in the data -- so they can be easily located and deleted.</p> <p>Let's look more closely at what is happening here. The first SELECT is implemented by the loop at instructions 3 through 8. Instruction 4 extracts the value of the "two" column from "examp" and instruction 5 converts this into a row. Instruction 6 pushes an empty string onto the stack. Finally, instruction 7 writes the row into the temporary table. But remember, the Put opcode uses the top of the stack as the GDBM data and the next on stack as the GDBM key. For an INSERT statement, the row generated by the MakeRecord opcode is the GDBM data and the GDBM key is an integer created by the New opcode. But here the roles are reversed and the row created by MakeRecord is the GDBM key and the GDBM data is just an empty string.</p> <p>The second SELECT is implemented by instructions 11 through 15. A new result row is created from the "four" column of table "examp2" by instructions 12 and 13. But instead of using Put to write this new row into the temporary table, we instead call Delete to remove it from the temporary table if it exists.</p> <p>The result of the compound select is sent to the callback routine by the loop at instructions 19 through 22. There is nothing new or remarkable about this loop, except for the fact that the Field instruction at 20 will be extracting a column out of the GDBM key rather than the GDBM data.</p> <h2>Summary</h2> <p>This article has reviewed all of the major techniques used by SQLite's VDBE to implement SQL statements. What has not been shown is that most of these techniques can be used in combination to generate code for an appropriately complex query statement. For example, we have shown how sorting is accomplished on a simple query and we have shown how to implement a compound query. But we did not give an example of sorting in a compound query. This is because sorting a compound query does not introduce any new concepts: it merely combines two previous ideas (sorting and compounding) in the same VDBE program.</p> <p>For additional information on how the SQLite library functions, the reader is directed to look at the SQLite source code directly. If you understand the material in this article, you should not have much difficulty in following the sources. Serious students of the internals of SQLite will probably also what to make a careful study of the VDBE opcodes as documented <a href="opcode.html">here</a>. Most of the opcode documentation is extracted from comments in the source code using a script so you can also get information about the various opcodes directly from the <b>vdbe.c</b> source file. If you have successfully read this far, you should have little difficulty understanding the rest.</p> <p>If you find errors in either the documentation or the code, feel free to fix them and/or contact the author at <a href="drh@hwaci.com">drh@hwaci.com</a>. Your bug fixes or suggestions are always welcomed.</p> } puts { <p><hr /></p> <p><a href="index.html"><img src="/goback.jpg" border=0 /> Back to the SQLite Home Page</a> </p> </body></html>} |