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One will show degree 1, the other will show the degree of parallelism set for the query (which may be derived from a hint, a specific degree of parallelism on a table, or the automatic degree dictated by Oracle if you have enabled parallel automatic tuning) Blocks to Sort: A measure of the data to be sorted Derived as Row size * Rows / block size If you have enabled parallelism, the value for Blocks to Sort in the second (parallel) set of figures will be the value from the first (serial) set of figures divided by the degree Row size: The optimizer s estimate of the average size of the rows to be sorted.

When casting away const or casting to a constant Conversions between compile-time compatible types Conversions with runtime check in inheritance hierarchies

You can mark Tasks complete by pressing the Menu key and selecting Mark Completed or, more easily, by highlighting the Task in the full list and pressing the Space key. TIP: Press the Space key again to uncheck a Task (mark it as incomplete).

Allowing for a couple of little adjustments and variations, this is derived from column avg_col_length of view user_tab_columns, and is usually (12 + sum(avg_col_length) + (n 1) ) (where n is the number of columns to be sorted) The fixed value 12 covers the cost of the tree node quite nicely, but the rest of the formula seems inappropriate as we have already seen that our 6 bytes of column data had a 2-byte column overhead and a 4- byte row overhead added It s just another spot where the model for calculation doesn t quite agree with the run-time activity..

When a Task alarm rings, you will see a popup window similar to the one shown to the right. At this point, you have three options: 1. Open the Task to change the due date, add notes, or edit anything else you want to. Click Mark Completed if you completed this Task. Click Dismiss to ignore this ringing Task alarm.

One difference between these two methods of gathering statistics is that the avg_col_len generated by the dbms_stats package includes the length byte, but the analyze command does not. Since the Row size used by the sort calculation uses the sum(avg_col_len) from view user_tab_columns, this means that the cost of a sort will be slightly higher following a call to dbms_stats than it would be if you carried on using the analyze command. (The difference is also relevant to hash joins.) There are lots of ways that the row size can be a bad estimate. For example, if you use a simple function of two columns (e.g., substr(col1 || col2,5,2)) the optimizer will add the column lengths of both columns in the calculation when it obviously ought to use the constant 2.

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Rows: This is the 1,048,576 that is the computed (filtered) cardinality for the table Again, if you have enabled parallelism, the value in the second (parallel) set of figures will be the value from the first (serial) set of figures divided by the degree Because the number of rows is scaled down while the Area size may stay unchanged, the cost of a parallel sort can easily be much lower than the cost of a serial sort even to the point where it is lower than the serial cost divided by the degree Initial runs: The optimizer s estimate of the number of sort runs that will be dumped to disk You can derive this as Blocks to Sort * block size / Max Area size (2,311 * 8,192 / 712,704 = 2656).

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In this example, the optimizer has managed to get the right (observed) result by using a strange number for the area size, and a wrong number for the row size Both values (Blocks to Sort and usable Area size) are larger than what actually occurs at run time Merge passes: Luckily, the Initial runs is less than the Sort width, so the optimizer has decided that all the runs can be merged in a single pass This is the significance of Merge passes Unfortunately, it always seems to be at least one even for an in-memory sort This figure counts the number of times the entire data set will be written to and read back from disk if you go into a multipass sort.