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traversing from an index root block to a leaf block. The first is HEIGHT, which is the number of blocks required to go from the root block to the leaf block. The HEIGHT value can be found from the INDEX_STATS view after the index has been analyzed using the ANALYZE INDEX <name> VALIDATE STRUCTURE command. The other is BLEVEL, which is the number of branch levels and differs from HEIGHT by one (it does not count the leaf blocks). The value of BLEVEL is found in the normal dictionary tables such as USER_INDEXES after statistics have been gathered.

while(rc == SQLITE_ROW) { for(i=0; i < ncols; i++) { fprintf(stderr, "'%s' ", sqlite3_column_text(stmt, i)); } fprintf(stderr, "\n"); } rc = sqlite3_step(stmt);

For example, say we have a 10,000,000-row table with a primary key index on a number column: big_table@ORA11GR2> select index_name, blevel, num_rows 2 from user_indexes 3 where table_name = 'BIG_TABLE'; INDEX_NAME BLEVEL NUM_ROWS ------------------------------ ---------- ---------BIG_TABLE_PK 2 10441513 The BLEVEL is 2, meaning the HEIGHT is 3, and it will take two I/Os to find a leaf (resulting in a third I/O). So we would expect three I/Os to retrieve any given key value from this index: big_table@ORA11GR2> select id from big_table where id = 42; Execution Plan ---------------------------------------------------------0 SELECT STATEMENT Optimizer=CHOOSE (Cost=2 Card=1 Bytes=6) 1 0 INDEX (UNIQUE SCAN) OF 'BIG_TABLE_PK' (UNIQUE) (Cost=2 Card=1 Bytes=6) Statistics --------------------------------------------------------- 3 consistent gets 1 rows processed

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Figure 1-1. Data organized in a table of rows and columns Each column in the source data must have a heading. You will be unable to create a pivot table if any of the heading cells are blank. No completely blank rows should be within the source data.

big_table@ORA11GR2> select id from big_table where id = 12345; Statistics --------------------------------------------------------- 3 consistent gets 1 rows processed big_table@ORA11GR2> select id from big_table where id = 1234567; Statistics --------------------------------------------------------- 3 consistent gets 1 rows processed The B*Tree is an excellent general-purpose indexing mechanism that works well for large and small tables, and experiences little, if any, degradation in retrieval performance as the size of the underlying table grows.

One of the interesting things you can do with a B*Tree index is compress it. This is not compression in the same manner that ZIP files are compressed; rather, this is compression that removes redundancies from concatenated (multicolumn) indexes. We covered compressed key indexes in some detail in the section Index Organized Tables in 10, and we will take a brief look at them again here. The basic concept behind a compressed key index is that every entry is broken into two pieces: a prefix and suffix component. The prefix is built on the leading columns of the concatenated index and will have many repeating values. The suffix is built on the trailing columns in the index key and is the unique component of the index entry within the prefix. By way of example, we ll create a table and a concatenated index and measure its space without compression using ANALYZE INDEX.

sqlite3_finalize(stmt); sqlite3_close(db); } return 0;

Note There is a common misperception that ANALYZE should not be used as a command in Oracle that the

DBMS_STATS package supersedes it. This is not true. What is true is that ANALYZE should not be used to gather statistics, but the other capabilities of ANALYZE still apply. The ANALYZE command should be used to perform operations such as validating the structure of an index (as we will below) or listing chained rows in a table. DBMS_STATS should be used exclusively to gather statistics on objects.

No completely blank columns can be within the source data. Each column must contain at least an entry in the heading cell. If you need the column to appear blank, you can type a heading, such as Blank1, and format the font with a color that matches the cell fill color.

We ll then re-create the index with index key compression, compressing a different number of key entries, and see the difference. Let s start with this table and index: ops$tkyte%ORA11GR2> create table t 2 as 3 select * from all_objects 4 where rownum <= 50000;

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