After implementing a pipelined top-N query to retrieve the first page efficiently, you will often also need another query to fetch the next pages. The resulting challenge is that it has to skip the rows from the previous pages. There are two different methods to meet this challenge: firstly the offset method, which numbers the rows from the beginning and uses a filter on this row number to discard the rows before the requested page. The second method, which I call the seek method, searches the last entry of the previous page and fetches only the following rows.
The following examples show the more widely used offset
method. Its main advantage is that it is very easy to handle—especially
with databases that have a dedicated keyword for it (
offset). This keyword was even taken into the
SQL standard as part of the
DB2 does not support the standard's
offsetsyntax. The only standard conforming alternative is the
ROW_NUMBER()window function (see next section). There are two other possibilities to get offset functionality, non of them recommendable: (1) using
db2set DB2_COMPATIBILITY_VECTOR=MYSto enable
offsetlike MySQL supports it. This does, however, not allow to combine
offset; (2) using
db2set DB2_COMPATIBILITY_VECTOR=ORAto get Oracle's
ROWNUMpseudo column (see Oracle example).
MySQL and PostgreSQL offer the
offsetclause for discarding the specified number of rows from the beginning of a top-N query. The
limitclause is applied afterwards.
SELECT * FROM sales ORDER BY sale_date DESC LIMIT 10 OFFSET 10
The Oracle database provides the pseudo column
ROWNUMthat numbers the rows in the result set automatically. It is, however, not possible to apply a greater than or equal to (
) filter on this pseudo-column. To make this work, you need to first “materialize” the row numbers by renaming the column with an alias.
SELECT * FROM ( SELECT tmp.*, rownum rn FROM ( SELECT * FROM sales ORDER BY sale_date DESC ) tmp WHERE rownum <= 20 ) WHERE rn > 10
Note the use of the alias
RNfor the lower bound and the
ROWNUMpseudo column itself for the upper bound .
fetch firstextension defines an
offset ... rowsclause as well. PostgreSQL, however, only accepts
rowskeyword. The previously used
limit/offsetsyntax still works as shown in the MySQL example.
SELECT * FROM sales ORDER BY sale_date DESC OFFSET 10 FETCH NEXT 10 ROWS ONLY
- SQL Server
SQL Server does not have an “offset” extension for its proprietary
topclause but introduced the
fetch firstextension with SQL Server 2012 (“Denali”). The
offsetclause is mandatory although the standard defines it as an optional addendum.
SELECT * FROM sales ORDER BY sale_date DESC OFFSET 10 ROWS FETCH NEXT 10 ROWS ONLY
Besides the simplicity, another advantage of this method is that you just need the row offset to fetch an arbitrary page. Nevertheless, the database must count all rows from the beginning until it reaches the requested page. Figure 7.2 shows that the scanned index range becomes greater when fetching more pages.
Figure 7.2 Access Using the Offset Method
This has two disadvantages: (1) the pages drift when inserting new sales because the numbering is always done from scratch; (2) the response time increases when browsing further back.
The seek method avoids both problems because it uses the
values of the previous page as a delimiter. That
means it searches for the values that must come
behind the last entry from the previous page. This can be
expressed with a simple
To put it the other way around: the seek method simply doesn't select
already shown values.
The next example shows the seek method. For the sake of
demonstration, we will start with the assumption that there is only one
sale per day. This makes the
SALE_DATE a unique key. To
select the sales that must come behind a particular date you must use a
less than condition (
<) because of the descending sort
order. For an ascending order, you would have to use a greater than
>) condition. The
first clause is just used to limit the result to ten
SELECT * FROM sales WHERE sale_date < ? ORDER BY sale_date DESC FETCH FIRST 10 ROWS ONLY
Instead of a row number, you use the last value of the previous page
to specify the lower bound. This has a huge benefit in terms of
performance because the database can use the
SALE_DATE < ?
condition for index access. That means that the database can truly skip
the rows from the previous pages. On top of that, you will also get stable
results if new rows are inserted.
Nevertheless, this method does not work if there is more than one
sale per day—as shown in Figure 7.2—because using the last date from the
first page (“yesterday”) skips all results from
yesterday—not just the ones already shown on the first page. The problem
is that the
order by clause does not
establish a deterministic row sequence. That is, however, prerequisite to
using a simple range condition for the page breaks.
Without a deterministic
clause, the database by definition does not deliver a deterministic row
sequence. The only reason you usually get a
consistent row sequence is that the database usually
executes the query in the same way. Nevertheless, the database could in
fact shuffle the rows having the same
SALE_DATE and still
order by clause. In recent
releases it might indeed happen that you get the result in a different
order every time you run the query, not because the database shuffles the
result intentionally but because the database might utilize parallel query
execution. That means that the same execution plan can result in a
different row sequence because the executing threads finish in a
Paging requires a deterministic sort order.
Even if the functional specifications only require sorting “by date,
latest first”, we as the developers must make sure the
order by clause yields a deterministic row
sequence. For this purpose, we might need to extend the
order by clause with arbitrary columns just to
make sure we get a deterministic row sequence. If the index that is used
for the pipelined
by has additional columns, it is a good start to add them to the
order by clause
so we can continue using this index for the pipelined
order by. If this still
does not yield a deterministic sort order, just add any unique column(s)
and extend the index accordingly.
In the following example, we extend the
order by clause and the index with the primary
SALE_ID to get a deterministic row sequence. Furthermore,
we must apply the “comes after” logic to both columns
together to get the desired result:
CREATE INDEX sl_dtid ON sales (sale_date, sale_id)
SELECT * FROM sales WHERE (sale_date, sale_id) < (?, ?) ORDER BY sale_date DESC, sale_id DESC FETCH FIRST 10 ROWS ONLY
where clause uses the
little-known “row values” syntax (see the box entitled “SQL Row Values”). It
combines multiple values into a logical unit that is applicable to the
regular comparison operators. As with scalar values, the less-than
condition corresponds to “comes after” when sorting in descending order.
That means the query considers only the sales that come after the given
Even though the row values syntax is part of the SQL standard, only a few databases support it. SQL Server 2012 (“Denali”) does not support row values at all. The Oracle database supports row values in principle, but cannot apply range operators on them (ORA-01796). MySQL evaluates row value expressions correctly but cannot use them as access predicate during an index access. DB2 (only LUW, since 10.1) and PostgreSQL (since 8.4), however, have a proper support of row value predicates and uses them to access the index if there is a corresponding index available.
Nevertheless it is possible to use an approximated variant of the seek method with databases that do not properly support the row values—even though the approximation is not as elegant and efficient as row values in PostgreSQL. For this approximation, we must use “regular” comparisons to express the required logic as shown in this Oracle example:
SELECT * FROM ( SELECT * FROM sales WHERE sale_date <= ? AND NOT (sale_date = ? AND sale_id >= ?) ORDER BY sale_date DESC, sale_id DESC ) WHERE rownum <= 10
where clause consists of two
parts. The first part considers the
SALE_DATE only and uses a
less than or equal to (
<=) condition—it selects more rows
as needed. This part of the
clause is simple enough so that all databases can use it to access the
index. The second part of the
clause removes the excess rows that were already shown on the previous
page. The box entitled “Indexing Equivalent Logic” explains why the
where clause is expressed this way.
The execution plan shows that the database uses the first part of
where clause as access
--------------------------------------------------------------- |Id | Operation | Name | Rows | Cost | --------------------------------------------------------------- | 0 | SELECT STATEMENT | | 10 | 4 | |*1 | COUNT STOPKEY | | | | | 2 | VIEW | | 10 | 4 | | 3 | TABLE ACCESS BY INDEX ROWID | SALES | 50218 | 4 | |*4 | INDEX RANGE SCAN DESCENDING| SL_DTIT | 2 | 3 | --------------------------------------------------------------- Predicate Information (identified by operation id): --------------------------------------------------- 1 - filter(ROWNUM<=10) 4 - access("SALE_DATE"<=:SALE_DATE) filter("SALE_DATE"<>:SALE_DATE OR "SALE_ID"<TO_NUMBER(:SALE_ID))
The access predicates on
SALE_DATE enables the database
to skip over the days that were fully shown on previous pages. The second
part of the
where clause is a filter
predicate only. That means that the database inspects a few entries from
the previous page again, but drops them immediately. Figure 7.3 shows the respective access
Figure 7.3 Access Using the Seek Method
Figure 7.4 compares the performance characteristics of the offset and the seek methods. The accuracy of measurement is insufficient to see the difference on the left hand side of the chart, however the difference is clearly visible from about page 20 onwards.
Figure 7.4 Scalability when Fetching the Next Page
whereclause very carefully—you also cannot fetch arbitrary pages. Moreover you need to reverse all comparison and sort operations to change the browsing direction. Precisely these two functions—skipping pages and browsing backwards—are not needed when using an infinite scrolling mechanism for the user interface.