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demonstrate that Oracle will limit the number of department keys per block based on my SIZE parameter above. Therefore, I needed more than the four department rows found in SCOTT.DEPT. I generated nine rows using the connect by level trick against DUAL and performed a Cartesian join of those nine rows with the four in DEPT resulting in 36 unique rows. I did a similar trick with EMP to fabricate data for these departments.

Instead of just retrying the call over and over, you can use a busy handler. Rather than having the API return SQLITE_BUSY if a connection cannot get a lock, you can get it to call the busy handler instead. A busy handler is a function you create that kills time or does whatever else you want it to do it can send spam to your mother-in-law for all SQLite cares. It s just going to get called when SQLite can t get a lock. The only thing the busy handler has to do is provide a return value, telling SQLite what to do next.

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Now that the data is loaded, let s look at the organization of it on disk. We ll use the DBMS_ROWID package to peek into the rowid and see what blocks data is stored on. Let s first look at the DEPT table and see how many DEPT rows per block we have: ops$tkyte%ORA11GR2> select min(count(*)), max(count(*)), avg(count(*)) 2 from dept 3 group by dbms_rowid.rowid_block_number(rowid) 4 / MIN(COUNT(*)) MAX(COUNT(*)) AVG(COUNT(*)) ------------- ------------- ------------1 7 6 So, even though we loaded DEPT first and the DEPT rows are very small (hundreds of them could fit on an 8k block normally) we find that the maximum number of DEPT rows on a block in this table is only seven. That fits in with what we anticipated above when we set the SIZE to 1024. We estimated that with an 8k block and 1024 bytes of data per cluster key for the combined EMP and DEPT records, we would see approximately seven unique cluster key values per block, and that is exactly what we are seeing here. Next, let s look at the EMP and DEPT table together. We ll look at the rowids of each and compare the block numbers after joining by DEPTNO. If the block numbers are the same, we ll know that the EMP row and the DEPT row are stored on the same physical database block together if they differ we ll know they are not. In this case, we observe that all of our data is perfectly stored. There are no cases where a record for the EMP table is stored on a block separate from its corresponding DEPT record: ops$tkyte%ORA11GR2> select * 2 from ( 3 select dept_blk, emp_blk, 4 case when dept_blk <> emp_blk then '*' end flag, 5 deptno

You can use programming to disable many pivot table features. For example, the following macro disables selection in each field in the first pivot table of the active sheet. The dropdown arrows disappear, and users can t change the displayed items. Store the code in a regular code module.

6 from ( 7 select dbms_rowidrowid_block_number(deptrowid) dept_blk, 8 dbms_rowidrowid_block_number(emprowid) emp_blk, 9 deptdeptno 10 from emp, dept 11 where empdeptno = deptdeptno 12 ) 13 ) 14 where flag = '*' 15 order by deptno 16 / no rows selected That was exactly our goal to get every row in the EMP table stored on the same block as the corresponding DEPT row But what would have happened if we estimated incorrectly, what if 1024 was insufficient What if some of our departments were close to 1024 and others exceeded that value Then, obviously, the data could not fit on the same block and we d have to place some of the EMP records on a block separate from the DEPT record.

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