MySQL 8.0.39
Source Code Documentation
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BufferingWindowIterator is like WindowIterator, but deals with window functions that need to buffer rows. More...
#include <window_iterators.h>
Public Member Functions | |
BufferingWindowIterator (THD *thd, unique_ptr_destroy_only< RowIterator > source, Temp_table_param *temp_table_param, JOIN *join, int output_slice) | |
bool | Init () override |
Initialize or reinitialize the iterator. More... | |
int | Read () override |
Read a single row. More... | |
void | SetNullRowFlag (bool is_null_row) override |
Mark the current row buffer as containing a NULL row or not, so that if you read from it and the flag is true, you'll get only NULLs no matter what is actually in the buffer (typically some old leftover row). More... | |
void | StartPSIBatchMode () override |
Start performance schema batch mode, if supported (otherwise ignored). More... | |
void | EndPSIBatchModeIfStarted () override |
Ends performance schema batch mode, if started. More... | |
void | UnlockRow () override |
Public Member Functions inherited from RowIterator | |
RowIterator (THD *thd) | |
virtual | ~RowIterator ()=default |
RowIterator (const RowIterator &)=delete | |
RowIterator (RowIterator &&)=default | |
virtual const IteratorProfiler * | GetProfiler () const |
Get profiling data for this iterator (for 'EXPLAIN ANALYZE'). More... | |
virtual void | SetOverrideProfiler ([[maybe_unused]] const IteratorProfiler *profiler) |
virtual RowIterator * | real_iterator () |
If this iterator is wrapping a different iterator (e.g. More... | |
virtual const RowIterator * | real_iterator () const |
Private Member Functions | |
int | ReadBufferedRow (bool new_partition_or_eof) |
Private Attributes | |
unique_ptr_destroy_only< RowIterator > const | m_source |
The iterator we are reading from. More... | |
Temp_table_param * | m_temp_table_param |
Parameters for the temporary table we are outputting to. More... | |
Window * | m_window |
The window function itself. More... | |
JOIN * | m_join |
The join we are a part of. More... | |
int | m_input_slice |
The slice we will be using when reading rows. More... | |
int | m_output_slice |
The slice we will be using when outputting rows. More... | |
bool | m_possibly_buffered_rows |
If true, we may have more buffered rows to process that need to be checked for before reading more rows from the source. More... | |
bool | m_last_input_row_started_new_partition |
Whether the last input row started a new partition, and was tucked away to finalize the previous partition; if so, we need to bring it back for processing before we read more rows. More... | |
bool | m_eof |
Whether we have seen the last input row. More... | |
Additional Inherited Members | |
Protected Member Functions inherited from RowIterator | |
THD * | thd () const |
BufferingWindowIterator is like WindowIterator, but deals with window functions that need to buffer rows.
If we don't need to buffer rows to evaluate the window functions, execution is simple; see WindowIterator for details. In that case, we can just evaluate the window functions as we go here, similar to the non-windowing flow.
If we do need buffering, though, we buffer the row in Read(). Next, we enter a loop calling process_buffered_windowing_record, and conditionally return the row. That is, if process_buffered_windowing_record was able to complete evaluation of a row (cf. output_row_ready), including its window functions given how much has already been buffered, we return a row, else we read more rows, and postpone evaluation and returning till we have enough rows in the buffer.
When we have read a full partition (or reach EOF), we evaluate any remaining rows. Note that since we have to read one row past the current partition to detect that that previous row was indeed the last row in a partition, we need to re-establish the first row of the next partition when we are done processing the current one. This is because the record will be overwritten (many times) during evaluation of window functions in the current partition.
Usually [1], for window execution we have two or three tmp tables per windowing step involved (although not all are always materialized; they may be just streaming through StreamingIterator):
[1] This is not always the case. For the first window, if we have no PARTITION BY or ORDER BY in the window, and there is more than one table in the join, the logical input can consist of more than one table (e.g. a NestedLoopIterator).
The first thing we do in Read() is: We copy fields from IN to OUT (copy_fields), and evaluate non-WF functions (copy_funcs): those functions then read their arguments from IN and store their result into their result_field which is a field in OUT.
Then, let's take SUM(A+FLOOR(B)) OVER (ROWS 2 FOLLOWING) as example. Above, we have stored A and the result of FLOOR in OUT. Now we buffer (save) the row from OUT into the FB: For that, we copy both field A and FLOOR's result_field from OUT to FB; a single copy_fields() call handles both copy jobs. Then we look at the rows we have buffered and may realize that we have enough of the frame to calculate SUM for a certain row (not necessarily the one we just buffered; might be an earlier row, in our example it is the row which is 2 rows above the buffered row). If we do, to calculate WFs, we bring back the frame's rows; which is done by: first copying field A and FLOOR's result_field back from FB to OUT, thus getting in OUT all that SUM needs (A and FLOOR), then giving that OUT row to SUM (SUM will then add the row's value to its total; that happens in copy_funcs). After we have done that on all rows of the frame, we have the values of SUM ready in OUT, we also restore the row which owns this SUM value, in the same way as we restored the frame's rows, and we return from Read() - we're done for this row. However, on the next Read() call, we loop to check if we can calculate one more row with the frame we have, and if so, we do, until we can't calculate any more rows – in which case we're back to just buffering.
BufferingWindowIterator::BufferingWindowIterator | ( | THD * | thd, |
unique_ptr_destroy_only< RowIterator > | source, | ||
Temp_table_param * | temp_table_param, | ||
JOIN * | join, | ||
int | output_slice | ||
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inlineoverridevirtual |
Ends performance schema batch mode, if started.
It's always safe to call this.
Iterators that have children (composite iterators) must forward the EndPSIBatchModeIfStarted() call to every iterator they could conceivably have called StartPSIBatchMode() on. This ensures that after such a call to on the root iterator, all handlers are out of batch mode.
Reimplemented from RowIterator.
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overridevirtual |
Initialize or reinitialize the iterator.
You must always call Init() before trying a Read() (but Init() does not imply Read()).
You can call Init() multiple times; subsequent calls will rewind the iterator (or reposition it, depending on whether the iterator takes in e.g. a Index_lookup) and allow you to read the records anew.
Implements RowIterator.
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overridevirtual |
Read a single row.
The row data is not actually returned from the function; it is put in the table's (or tables', in case of a join) record buffer, ie., table->records[0].
0 | OK |
-1 | End of records |
1 | Error |
Implements RowIterator.
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private |
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inlineoverridevirtual |
Mark the current row buffer as containing a NULL row or not, so that if you read from it and the flag is true, you'll get only NULLs no matter what is actually in the buffer (typically some old leftover row).
This is used for outer joins, when an iterator hasn't produced any rows and we need to produce a NULL-complemented row. Init() or Read() won't necessarily reset this flag, so if you ever set is to true, make sure to also set it to false when needed.
Note that this can be called without Init() having been called first. For example, NestedLoopIterator can hit EOF immediately on the outer iterator, which means the inner iterator doesn't get an Init() call, but will still forward SetNullRowFlag to both inner and outer iterators.
TODO: We shouldn't need this. See the comments on AggregateIterator for a bit more discussion on abstracting out a row interface.
Implements RowIterator.
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inlineoverridevirtual |
Start performance schema batch mode, if supported (otherwise ignored).
PFS batch mode is a mitigation to reduce the overhead of performance schema, typically applied at the innermost table of the entire join. If you start it before scanning the table and then end it afterwards, the entire set of handler calls will be timed only once, as a group, and the costs will be distributed evenly out. This reduces timer overhead.
If you start PFS batch mode, you must also take care to end it at the end of the scan, one way or the other. Do note that this is true even if the query ends abruptly (LIMIT is reached, or an error happens). The easiest workaround for this is to simply call EndPSIBatchModeIfStarted() on the root iterator at the end of the scan. See the PFSBatchMode class for a useful helper.
The rules for starting batch and ending mode are:
The upshot of this is that when scanning a single table, batch mode will typically be activated for that table (since we call StartPSIBatchMode() on the root iterator, and it will trickle all the way down to the table iterator), but for a join, the call will be ignored and the join iterator will activate batch mode by itself as needed.
Reimplemented from RowIterator.
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inlineoverridevirtual |
Implements RowIterator.
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Whether we have seen the last input row.
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The slice we will be using when reading rows.
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The join we are a part of.
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Whether the last input row started a new partition, and was tucked away to finalize the previous partition; if so, we need to bring it back for processing before we read more rows.
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The slice we will be using when outputting rows.
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If true, we may have more buffered rows to process that need to be checked for before reading more rows from the source.
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The iterator we are reading from.
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Parameters for the temporary table we are outputting to.
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The window function itself.