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<title>Berkeley DB Reference Guide: Degrees of isolation</title>
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<td><dl><dt>Berkeley DB Reference Guide:<dd>Berkeley DB Transactional Data Store Applications</dl></td>
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Degrees of isolation
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Transactions can be isolated from each other to different degrees.
Serializable provides the most isolation, and means that, for
the life of the transaction, every time a thread of control reads a data
item, it will be unchanged from its previous value (assuming, of course,
the thread of control does not itself modify the item). By default,
Berkeley DB enforces serializability whenever database reads are wrapped in
transactions. This is also known as degree 3 isolation.
Most applications do not need to enclose all reads in transactions, and
when possible, transactionally protected reads at serializable isolation
should be avoided as they can cause performance problems. For example,
a serializable cursor sequentially reading each key/data pair in a
database, will acquire a read lock on most of the pages in the database
and so will gradually block all write operations on the databases until
the transaction commits or aborts. Note, however, that if there are
update transactions present in the application, the read operations must
still use locking, and must be prepared to repeat any operation
(possibly closing and reopening a cursor) that fails with a return value
of <a href="../../ref/program/errorret.html#DB_LOCK_DEADLOCK">DB_LOCK_DEADLOCK</a>. Applications that need repeatable reads
are ones that require the ability to repeatedly access a data item
knowing that it will not have changed (for example, an operation
modifying a data item based on its existing value).
Snapshot isolation also guarantees repeatable reads, but
avoids read locks by using multiversion concurrency control (MVCC).
This makes update operations more expensive, because they have to
allocate space for new versions of pages in cache and make copies, but
avoiding read locks can significantly increase throughput for many
applications. Snapshot isolation is discussed in detail below.
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A transaction may only require cursor stability, that is only
be guaranteed that cursors see committed data that does not change so
long as it is addressed by the cursor, but may change before the reading
transaction completes. This is also called degree 2
isolation. Berkeley DB provides this level of isolation when a transaction
is started with the <a href="../../api_c/db_cursor.html#DB_READ_COMMITTED">DB_READ_COMMITTED</a> flag. This flag may also
be specified when opening a cursor within a fully isolated
transaction.
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Berkeley DB optionally supports reading uncommitted data; that is, read
operations may request data which has been modified but not yet
committed by another transaction. This is also called degree
1 isolation. This is done by first specifying the
<a href="../../api_c/db_open.html#DB_READ_UNCOMMITTED">DB_READ_UNCOMMITTED</a> flag when opening the underlying database,
and then specifying the <a href="../../api_c/db_open.html#DB_READ_UNCOMMITTED">DB_READ_UNCOMMITTED</a> flag when beginning
a transaction, opening a cursor, or performing a read operation. The
advantage of using <a href="../../api_c/db_open.html#DB_READ_UNCOMMITTED">DB_READ_UNCOMMITTED</a> is that read operations
will not block when another transaction holds a write lock on the
requested data; the disadvantage is that read operations may return data
that will disappear should the transaction holding the write lock
abort.
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Snapshot Isolation
To make use of snapshot isolation, databases must first be configured
for multiversion access by calling <a href="../../api_c/db_open.html">DB-&gt;open</a> with the
<a href="../../api_c/db_open.html#DB_MULTIVERSION">DB_MULTIVERSION</a> flag. Then transactions or cursors must be
configured with the <a href="../../api_c/txn_begin.html#DB_TXN_SNAPSHOT">DB_TXN_SNAPSHOT</a> flag.
When configuring an environment for snapshot isolation, it is important
to realize that having multiple versions of pages in cache means that
the working set will take up more of the cache. As a result, snapshot
isolation is best suited for use with larger cache sizes.
If the cache becomes full of page copies before the old copies can be
discarded, additional I/O will occur as pages are written to temporary
"freezer" files. This can substantially reduce throughput, and should
be avoided if possible by configuring a large cache and keeping snapshot
isolation transactions short. The amount of cache required to avoid
freezing buffers can be estimated by taking a checkpoint followed by a
call to <a href="../../api_c/log_archive.html">DB_ENV-&gt;log_archive</a>. The amount of cache required is
approximately double the size of logs that remains.
The environment should also be configured for sufficient transactions
using <a href="../../api_c/env_set_tx_max.html">DB_ENV-&gt;set_tx_max</a>. The maximum number of transactions
needs to include all transactions executed concurrently by the
application plus all cursors configured for snapshot isolation.
Further, the transactions are retained until the last page they created
is evicted from cache, so in the extreme case, an additional transaction
may be needed for each page in the cache. Note that cache sizes under
500MB are increased by 25%, so the calculation of number of pages needs
to take this into account.
So when should applications use snapshot isolation?
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<li>There is a large cache relative to size of updates performed by
concurrent transactions; and
<li>Read/write contention is limiting the throughput of the application;
or
<li>The application is all or mostly read-only, and contention for the lock
manager mutex is limiting throughput.
</ul>
The simplest way to take advantage of snapshot isolation is for queries:
keep update transactions using full read/write locking and set
<a href="../../api_c/txn_begin.html#DB_TXN_SNAPSHOT">DB_TXN_SNAPSHOT</a> on read-only transactions or cursors. This
should minimize blocking of snapshot isolation transactions and will
avoid introducing new <a href="../../ref/program/errorret.html#DB_LOCK_DEADLOCK">DB_LOCK_DEADLOCK</a> errors.
If the application has update transactions which read many items and
only update a small set (for example, scanning until a desired record is
found, then modifying it), throughput may be improved by running some
updates at snapshot isolation as well.
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