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Add discussion and example about predicate locking and why "serializable"

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mode isn't really serializable.  I had thought this was covered already
in our docs, but I sure can't find it.
This commit is contained in:
Tom Lane 2004-08-14 22:18:23 +00:00
parent 11d8138ca3
commit 793dd8e729
1 changed files with 100 additions and 14 deletions
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114
doc/src/sgml/mvcc.sgml
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@ -1,5 +1,5 @@
<!--
$PostgreSQL: pgsql/doc/src/sgml/mvcc.sgml,v 2.43 2003/12/13 23:59:06 neilc Exp $
$PostgreSQL: pgsql/doc/src/sgml/mvcc.sgml,v 2.44 2004/08/14 22:18:23 tgl Exp $
-->
<chapter id="mvcc">
@ -394,6 +394,90 @@ ERROR: could not serialize access due to concurrent update
a transaction executes several successive commands that must see
identical views of the database.
</para>
<sect3 id="mvcc-serializability">
<title>Serializable Isolation versus True Serializability</title>
<indexterm>
<primary>serializability</primary>
</indexterm>
<indexterm>
<primary>predicate locking</primary>
</indexterm>
<para>
The intuitive meaning (and mathematical definition) of
<quote>serializable</> execution is that any two successfully committed
concurrent transactions will appear to have executed strictly serially,
one after the other --- although which one appeared to occur first may
not be predictable in advance. It is important to realize that forbidding
the undesirable behaviors listed in <xref linkend="mvcc-isolevel-table">
is not sufficient to guarantee true serializability, and in fact
<productname>PostgreSQL</productname>'s Serializable mode <emphasis>does
not guarantee serializable execution in this sense</>. As an example,
consider a table <structname>mytab</>, initially containing
<screen>
class | value
-------+-------
1 | 10
1 | 20
2 | 100
2 | 200
</screen>
Suppose that serializable transaction A computes
<screen>
SELECT SUM(value) FROM mytab WHERE class = 1;
</screen>
and then inserts the result (30) as the <structfield>value</> in a
new row with <structfield>class</> = 2. Concurrently, serializable
transaction B computes
<screen>
SELECT SUM(value) FROM mytab WHERE class = 2;
</screen>
and obtains the result 300, which it inserts in a new row with
<structfield>class</> = 1. Then both transactions commit. None of
the listed undesirable behaviors have occurred, yet we have a result
that could not have occurred in either order serially. If A had
executed before B, B would have computed the sum 330, not 300, and
similarly the other order would have resulted in a different sum
computed by A.
</para>
<para>
To guarantee true mathematical serializability, it is necessary for
a database system to enforce <firstterm>predicate locking</>, which
means that a transaction cannot insert or modify a row that would
have matched the <literal>WHERE</> condition of a query in another concurrent
transaction. For example, once transaction A has executed the query
<literal>SELECT ... WHERE class = 1</>, a predicate-locking system
would forbid transaction B from inserting any new row with class 1
until A has committed.
<footnote>
<para>
Essentially, a predicate-locking system prevents phantom reads
by restricting what is written, whereas MVCC prevents them by
restricting what is read.
</para>
</footnote>
Such a locking system is complex to
implement and extremely expensive in execution, since every session must
be aware of the details of every query executed by every concurrent
transaction. And this large expense is mostly wasted, since in
practice most applications do not do the sorts of things that could
result in problems. (Certainly the example above is rather contrived
and unlikely to represent real software.) Accordingly,
<productname>PostgreSQL</productname> does not implement predicate
locking, and so far as we are aware no other production DBMS does either.
</para>
<para>
In those cases where the possibility of nonserializable execution
is a real hazard, problems can be prevented by appropriate use of
explicit locking. Further discussion appears in the following
sections.
</para>
</sect3>
</sect2>
</sect1>
@ -434,7 +518,8 @@ ERROR: could not serialize access due to concurrent update
<para>
The list below shows the available lock modes and the contexts in
which they are used automatically by
<productname>PostgreSQL</productname>.
<productname>PostgreSQL</productname>. You can also acquire any
of these locks explicitly with the command <xref linkend="sql-lock">.
Remember that all of these lock modes are table-level locks,
even if the name contains the word
<quote>row</quote>; the names of the lock modes are historical.
@ -736,8 +821,8 @@ UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
<para>
The best defense against deadlocks is generally to avoid them by
being certain that all applications using a database acquire
locks on multiple objects in a consistent order. That was the
reason for the previous deadlock example: if both transactions
locks on multiple objects in a consistent order. In the example
above, if both transactions
had updated the rows in the same order, no deadlock would have
occurred. One should also ensure that the first lock acquired on
an object in a transaction is the highest mode that will be
@ -778,7 +863,7 @@ UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
Another way to think about it is that each
transaction sees a snapshot of the database contents, and concurrently
executing transactions may very well see different snapshots. So the
whole concept of <quote>now</quote> is somewhat suspect anyway.
whole concept of <quote>now</quote> is somewhat ill-defined anyway.
This is not normally
a big problem if the client applications are isolated from each other,
but if the clients can communicate via channels outside the database
@ -801,8 +886,8 @@ UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
</para>
<para>
Global validity checks require extra thought under <acronym>MVCC</acronym>. For
example, a banking application might wish to check that the sum of
Global validity checks require extra thought under <acronym>MVCC</acronym>.
For example, a banking application might wish to check that the sum of
all credits in one table equals the sum of debits in another table,
when both tables are being actively updated. Comparing the results of two
successive <literal>SELECT sum(...)</literal> commands will not work reliably under
@ -824,9 +909,9 @@ UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
<para>
Note also that if one is
relying on explicit locks to prevent concurrent changes, one should use
relying on explicit locking to prevent concurrent changes, one should use
Read Committed mode, or in Serializable mode be careful to obtain the
lock(s) before performing queries. An explicit lock obtained in a
lock(s) before performing queries. A lock obtained by a
serializable transaction guarantees that no other transactions modifying
the table are still running, but if the snapshot seen by the
transaction predates obtaining the lock, it may predate some now-committed
@ -834,7 +919,7 @@ UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
frozen at the start of its first query or data-modification command
(<literal>SELECT</>, <literal>INSERT</>,
<literal>UPDATE</>, or <literal>DELETE</>), so
it's possible to obtain explicit locks before the snapshot is
it's possible to obtain locks explicitly before the snapshot is
frozen.
</para>
</sect1>
@ -888,10 +973,11 @@ UPDATE accounts SET balance = balance - 100.00 WHERE acctnum = 22222;
</term>
<listitem>
<para>
Share/exclusive page-level locks are used for read/write
access. Locks are released after the page is processed.
Page-level locks provide better concurrency than index-level
ones but are liable to deadlocks.
Share/exclusive hash-bucket-level locks are used for read/write
access. Locks are released after the whole bucket is processed.
Bucket-level locks provide better concurrency than index-level
ones, but deadlock is possible since the locks are held longer
than one index operation.
</para>
</listitem>
</varlistentry>