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  <TITLE>Transactions and Other Access Contexts

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<A NAME="4"><!-- Empty --></A>
<H2>4 Transactions and Other Access Contexts

</H2>

<P>This chapter describes the Mnesia transaction system and the
transaction properties which make Mnesia a fault tolerant,
distributed database management system. 


<P>Also covered in this chapter are the locking functions, 
including table locks and sticky locks, as well as alternative
functions which bypass the transaction system in favor of improved
speed and reduced overheads. These functions are called &#34;dirty
operations&#34;. We also describe the usage of nested transactions. 
This chapter contains the following sections: 


<P>
<UL>

<LI>
transaction properties, which include atomicity,
consistency, isolation, and durability


</LI>


<LI>
Locking


</LI>


<LI>
Dirty operations


</LI>


<LI>
Record names vs table names


</LI>


<LI>
Activity concept and various access contexts


</LI>


<LI>
Nested transactions


</LI>


<LI>
Pattern matching


</LI>


<LI>
Iteration 


</LI>


</UL>
<A NAME="trans_prop"><!-- Empty --></A><A NAME="4.1"><!-- Empty --></A>
<H3>4.1 Transaction Properties</H3>

<P>Transactions are an important tool when designing fault
tolerant, distributed systems. A Mnesia transaction is a mechanism
by which a series of database operations can be executed as one
functional block. The functional block which is run as a
transaction is called a Functional Object (Fun), and this code can
read, write, or delete Mnesia records. The Fun is evaluated as a
transaction which either commits, or aborts. If a transaction 
succeeds in executing Fun it will replicate the action on all nodes
involved, or abort if an error occurs. 


<P>The following example shows a transaction which raises the
salary of certain employee numbers. 


<PRE>
raise(Eno, Raise) -&#62;
    F = fun() -&#62;
                [E] = mnesia:read(employee, Eno, write),
                Salary = E#employee.salary + Raise,
                New = E#employee{salary = Salary},
                mnesia:write(New)
        end,
    mnesia:transaction(F).

</PRE>

<P>The transaction <CODE>raise(Eno, Raise) - &#62;</CODE> contains a Fun
made up of four lines of code. This Fun is called by the statement
<CODE>mnesia:transaction(F)</CODE> and returns a value. 


<P>The Mnesia transaction system facilitates the construction of
reliable, distributed systems by providing the following important
properties: 


<P>
<UL>

<LI>
The transaction handler ensures that a Fun which is placed
inside a transaction does not interfere with operations embedded
in other transactions when it executes a series of operations on
tables. 


</LI>


<LI>
The transaction handler ensures that either all operations
in the transaction are performed successfully on all nodes
atomically, or the transaction fails without permanent effect on
any of the nodes. 


</LI>


<LI>
The Mnesia transactions have four important properties,
which we call <STRONG>A</STRONG>tomicity,
<STRONG>C</STRONG>onsistency,<STRONG>I</STRONG>solation, and
<STRONG>D</STRONG>urability, or ACID for short. These properties are
described in the following sub-sections.

</LI>


</UL>
<A NAME="4.1.1"><!-- Empty --></A>
<H4>4.1.1 Atomicity</H4>

<P><STRONG>Atomicity</STRONG> means that database changes which are
        executed by a transaction take effect on all nodes involved, or
        on none of the nodes. In other words, the transaction either
        succeeds entirely, or it fails entirely. 


<P>Atomicity is particularly important when we want to
        atomically write more than one record in the same
        transaction. The <CODE>raise/2</CODE> function, shown as an example
        above, writes one record only. The <CODE>insert_emp/3</CODE> function,
        shown in the program listing in Chapter 2, writes the record
        <CODE>employee</CODE> as well as employee relations such as
        <CODE>at_dep</CODE> and <CODE>in_proj</CODE> into the database. If we run
        this latter code inside a transaction, then the transaction
        handler ensures that the transaction either succeeds completely,
        or not at all. 


<P>Mnesia is a distributed DBMS where data can be replicated on
        several nodes. In many such applications, it is important that a
        series of write operations are performed atomically inside a
        transaction. The atomicity property ensures that a transaction
        take effect on all nodes, or none at all. 
<A NAME="4.1.2"><!-- Empty --></A>
<H4>4.1.2 Consistency</H4>

<P><STRONG>Consistency</STRONG>. This transaction property ensures that
        a transaction always leaves the DBMS in a consistent state. For
        example, Mnesia ensures that inconsistencies will not occur if
        Erlang, Mnesia or the computer crashes while a write operation
        is in progress.

<A NAME="4.1.3"><!-- Empty --></A>
<H4>4.1.3 Isolation</H4>

<P><STRONG>Isolation</STRONG>. This transaction property ensures that
        transactions which execute on different nodes in a network, and
        access and manipulate the same data records, will not interfere
        with each other. 


<P>The isolation property makes it possible to concurrently execute 
the <CODE>raise/2</CODE> function. A classical problem in concurrency control
theory is the so called &#34;lost update problem&#34;. 


<P>The isolation property is extremely useful if the following 
        circumstances occurs where an employee (with an employee number
        123) and two processes, (P1 and P2), are concurrently trying to 
        raise the salary for the employee. The initial value of the
employees salary is, for example, 5. Process P1 then starts to execute,
it reads the employee record and adds 2 to the salary. At this
point in time, process P1 is for some reason preempted and
process P2 has the opportunity to run. P2 reads the record, adds 3
to the salary, and finally writes a new employee record with
the salary set to 8. Now, process P1 start to run again and
writes its employee record with salary set to 7, thus
effectively overwriting and undoing the work performed by
process P2. The update performed by P2 is lost. 


<P>A transaction system makes it possible to concurrently
        execute two or more processes which manipulate the same
        record. The programmer does not need to check that the
        updates are synchronous, this is overseen by the
        transaction handler. All programs accessing the database through
        the transaction system may be written as if they had sole access
        to the data.

<A NAME="4.1.4"><!-- Empty --></A>
<H4>4.1.4 Durability</H4>

<P><STRONG>Durability</STRONG>. This transaction property ensures that
        changes made to the DBMS by a transaction are permanent. Once a
        transaction has been committed, all changes made to the database
         are durable - i.e. they are written safely to disc and will not
        be corrupted or disappear. 


<P>
<TABLE CELLPADDING=4>
  <TR>
    <TD VALIGN=TOP><IMG ALT="Note!" SRC="note.gif"></TD>
    <TD>

<P>The durability feature described does not entirely apply to
         situations where Mnesia is configured as a &#34;pure&#34; primary memory
         database. 

    </TD>
  </TR>
</TABLE>
<A NAME="4.2"><!-- Empty --></A>
<H3>4.2 Locking</H3>

<P>Different transaction managers employ different strategies to
satisfy the isolation property. Mnesia uses the standard technique
of two-phase locking. This means that locks are set on records
before they are read or written. Mnesia uses five different kinds
of locks. 


<P>
<UL>

<LI>
<STRONG>Read locks</STRONG>. A read lock is set on one replica of
a record before it can be read.


</LI>


<LI>
<STRONG>Write locks</STRONG>. Whenever a transaction writes to an
record, write locks are first set on all replicas of that
particular record. 


</LI>


<LI>
<STRONG>Read table locks</STRONG>. If a transaction traverses an
entire table in search for a record which satisfy some
particular property, it is most inefficient to set read locks on
the records, one by one. It is also very memory consuming, since
the read locks themselves may take up considerable space if the
table is very large. For this reason, Mnesia can set a read lock
on an entire table. 


</LI>


<LI>
<STRONG>Write table locks</STRONG>. If a transaction writes a
large number of records to one table, it is possible to set a
write lock on the entire table. 


</LI>


<LI>
<STRONG>Sticky locks</STRONG>. These are write locks that stay in
place at a node after the transaction which initiated the lock
has terminated. 

</LI>


</UL>

<P>Mnesia employs a strategy whereby functions such as
<CODE>mnesia:read/1</CODE> acquire the necessary locks dynamically as
the transactions execute. Mnesia automatically sets and releases
the locks and the programmer does not have to code these
operations. 


<P>Deadlocks can occur when concurrent processes set and release
locks on the same records. Mnesia employs a &#34;wait-die&#34; strategy to
resolve these situations. If Mnesia suspects that a deadlock can
occur when a transaction tries to set a lock, the transaction is
forced to release all its locks and sleep for a while. The
Fun in the transaction will be evaluated one more time. 


<P>For this reason, it is important that the code inside the Fun given to
<CODE>mnesia:transaction/1</CODE> is pure. Some strange results can
occur if, for example, messages are sent by the transaction
Fun. The following example illustrates this situation: 


<PRE>
bad_raise(Eno, Raise) -&#62;
    F = fun() -&#62;
                [E] = mnesia:read({employee, Eno}),
                Salary = E#employee.salary + Raise,
                New = E#employee{salary = Salary},
                io:format(&#34;Trying to write ... ~n&#34;, []),
                mnesia:write(New)
        end,
    mnesia:transaction(F).

</PRE>

<P>This transaction could write the text <CODE>&#34;Trying to write
... &#34;</CODE> a thousand times to the terminal. Mnesia does guarantee,
however, that each and every transaction will eventually run. As a
result, Mnesia is not only deadlock free, but also livelock
free.


<P>The Mnesia programmer cannot prioritize one particular
transaction to execute before other transactions which are waiting
to execute. As a result, the Mnesia DBMS transaction system is not
suitable for hard real time applications. However, Mnesia contains
other features that have real time properties. 


<P>Mnesia dynamically sets and releases locks as
transactions execute, therefore, it is very dangerous to execute code with
transaction side-effects. In particular, a <CODE>receive</CODE>
statement inside a transaction can lead to a situation where the
transaction hangs and never returns, which in turn can cause locks
not to release. This situation could bring the whole system to a
standstill since other transactions which execute in other
processes, or on other nodes, are forced to wait for the defective
transaction. 


<P>If a transaction terminates abnormally, Mnesia will
automatically release the locks held by the transaction. 


<P>We have shown examples of a number of functions that can be
used inside a transaction. The following list shows the
<STRONG>simplest</STRONG> Mnesia functions that work with transactions. It
is important to realize that these functions must be embedded in a
transaction. If no enclosing transaction (or other enclosing
Mnesia activity) exists, they will all fail.


<P>
<UL>

<LI>
<CODE>mnesia:transaction(Fun) -&#62; {aborted, Reason} |{atomic,
Value}</CODE>. This function executes one transaction with the
functional object <CODE>Fun</CODE> as the single parameter. 


</LI>


<LI>
<CODE>mnesia:read({Tab, Key}) -&#62; transaction abort |
RecordList</CODE>. This function reads all records with <CODE>Key</CODE>
as key from table <CODE>Tab</CODE>. This function has the same semantics
regardless of the location of <CODE>Table</CODE>. If the table is of
type <CODE>bag</CODE>, the <CODE>read({Tab, Key})</CODE> can return an arbitrarily
long list. If the table is of type <CODE>set</CODE>, the list is
either of length one, or <CODE>[]</CODE>.


</LI>


<LI>
<CODE>mnesia:wread({Tab, Key}) -&#62; transaction abort |
RecordList</CODE>. This function behaves the same way as the
previously listed <CODE>read/1</CODE> function, except that it
acquires a write lock instead of a read lock. If we execute a
transaction which reads a record, modifies the record, and then
writes the record, it is slightly more efficient to set the
write lock immediately. In cases where we issue a
<CODE>mnesia:read/1</CODE>, followed by a <CODE>mnesia:write/1</CODE>, the
first read lock must be upgraded to a write lock when the write
operation is executed. 


</LI>


<LI>
<CODE>mnesia:write(Record) -&#62; transaction abort |
ok</CODE>. This function writes a record into the database. The
<CODE>Record</CODE> argument is an instance of a record. The function
returns <CODE>ok</CODE>, or aborts the transaction if an error should
occur. 


</LI>


<LI>
<CODE>mnesia:delete({Tab, Key}) -&#62; transaction abort | ok</CODE>. This
function deletes all records with the given key.


</LI>


<LI>
<CODE>mnesia:delete_object(Record) -&#62; transaction abort |
ok</CODE>. This function deletes records with object id
<CODE>Record</CODE>. This function is used when we want to delete only
some records in a table of type <CODE>bag</CODE>. 

</LI>


</UL>
<A NAME="4.2.1"><!-- Empty --></A>
<H4>4.2.1 Sticky Locks</H4>

<P>As previously stated, the locking strategy used by Mnesia is
to lock one record when we read a record, and lock all replicas
of a record when we write a record. However, there are
applications which use Mnesia mainly for its fault-tolerant
qualities, and these applications may be configured with one
node doing all the heavy work, and a standby node which is ready
to take over in case the main node fails. Such applications may
benefit from using sticky locks instead of the normal locking
scheme. 


<P>A sticky lock is a lock which stays in place at a node after
the transaction which first acquired the lock has terminated. To
illustrate this, assume that we execute the following
transaction: 


<PRE>
        F = fun() -&#62;
              mnesia:write(#foo{a = kalle})
            end,
        mnesia:transaction(F).
      
</PRE>

<P>The <CODE>foo</CODE> table is replicated on the two nodes <CODE>N1</CODE>
and <CODE>N2</CODE>. 
        
        <BR>
Normal locking requires: 


<P>
<UL>

<LI>
one network rpc (2 messages) to acquire the write lock


</LI>


<LI>
three network messages to execute the two-phase commit protocol.


</LI>


</UL>

<P>If we use sticky locks, we must first change the code as follows:


<PRE>

        F = fun() -&#62;
              mnesia:s_write(#foo{a = kalle})
            end,
        mnesia:transaction(F).
      
</PRE>

<P>This code uses the <CODE>s_write/1</CODE> function instead of the
        <CODE>write/1</CODE> function. The <CODE>s_write/1</CODE> function sets a
        sticky lock instead of a normal lock. If the table is not
        replicated, sticky locks have no special effect. If the table is
        replicated, and we set a sticky lock on node <CODE>N1</CODE>, this
        lock will then stick to node <CODE>N1</CODE>. The next time we try to
        set a sticky lock on the same record at node <CODE>N1</CODE>, Mnesia
        will see that the lock is already set and will not do a network
        operation in order to acquire the lock. 


<P>It is much more efficient to set a local lock than it is to set
        a networked lock, and for this reason sticky locks can benefit 
        application that use a replicated table and perform most of the
        work on only one of the nodes. 


<P>If a record is stuck at node <CODE>N1</CODE> and we try to set a
        sticky lock for the record on node <CODE>N2</CODE>, the record must be
        unstuck. This operation is expensive and will reduce performance. The unsticking is
        done automatically if we issue <CODE>s_write/1</CODE> requests at
        <CODE>N2</CODE>.

<A NAME="4.2.2"><!-- Empty --></A>
<H4>4.2.2 Table Locks</H4>

<P>Mnesia supports read and write locks on whole tables as a
        complement to the normal locks on single records. As previously
        stated, Mnesia sets and releases locks automatically, and the
        programmer does not have to code these operations. However,
        transactions which read and write a large number of records in a
        specific table will execute more efficiently if we start the
        transaction by setting a table lock on this table. This will
        block other concurrent transactions from the table. The
        following two function are used to set explicit table locks for
        read and write operations:


<P>
<UL>

<LI>
<CODE>mnesia:read_lock_table(Tab)</CODE> Sets a read lock on
the table <CODE>Tab</CODE>


</LI>


<LI>
<CODE>mnesia:write_lock_table(Tab)</CODE> Sets a write lock on
the table <CODE>Tab</CODE>


</LI>


</UL>

<P>Alternate syntax for acquisition of table locks is as follows:


<PRE>
        mnesia:lock({table, Tab}, read)
        mnesia:lock({table, Tab}, write)
      
</PRE>

<P>The matching operations in Mnesia may either lock the entire
table or just a single record (when the key is bound in the
pattern).

<A NAME="4.2.3"><!-- Empty --></A>
<H4>4.2.3 Global Locks</H4>

<P>Write locks are normally acquired on all nodes where a
replica of the table resides (and is active). Read locks are
acquired on one node (the local one if a local
replica exists).


<P>The function <CODE>mnesia:lock/2</CODE> is intended to support
table locks (as mentioned previously)
but also for situations when locks need to be
acquired regardless of how tables have been replicated:


<PRE>
        mnesia:lock({global, GlobalKey, Nodes}, LockKind)

        LockKind ::= read | write | ...
        
</PRE>

<P>The lock is acquired on the LockItem on all Nodes in the
nodes list.
<A NAME="4.3"><!-- Empty --></A>
<H3>4.3 Dirty Operations</H3>

<P>In many applications, the overhead of processing a transaction
may result in a loss of performance. Dirty operation are short 
cuts which bypass much of the processing and increase the speed 
of the transaction.


<P>Dirty operation are useful in many situations, for example in a datagram routing
application where Mnesia stores the routing table, and it is time 
consuming to start a whole transaction every time a packet is
received. For this reason, Mnesia has functions which manipulate
tables without using transactions. This alternative
to processing is known as a dirty operation. However, it is important to
realize the trade-off in avoiding the overhead of transaction
processing: 


<P>
<UL>

<LI>
The atomicity and the isolation properties of Mnesia are lost.


</LI>


<LI>
The isolation property is compromised, because other
Erlang processes, which use transaction to manipulate the data,
do not get the benefit of isolation if we simultaneously use
dirty operations to read and write records from the same table. 


</LI>


</UL>

<P>The major advantage of dirty operations is that they execute
much faster than equivalent operations that are processed as 
functional objects within a transaction. 


<P>Dirty operations
are written to disc if they are performed on a table of type
<CODE>disc_copies</CODE>, or type <CODE>disc_only_copies</CODE>. Mnesia also
ensures that all replicas of a table are updated if a
dirty write operation is performed on a table.


<P>A dirty operation will ensure a certain level of consistency. 
For example, it is not possible for dirty operations to return 
garbled records. Hence, each individual read or write operation 
is performed in an atomic manner. 


<P>All dirty functions execute a call to <CODE>exit({aborted,
        Reason})</CODE> on failure. Even if the following functions are
executed inside a transaction no locks will be aquired. The
following functions are available:


<P>
<UL>

<LI>
<CODE>mnesia:dirty_read({Tab, Key})</CODE>. This function reads
record(s) from Mnesia.


</LI>


<LI>
<CODE>mnesia:dirty_write(Record)</CODE>. This function writes
the record <CODE>Record</CODE>


</LI>


<LI>
<CODE>mnesia:dirty_delete({Tab, Key})</CODE>. This function deletes
record(s) with the key <CODE>Key</CODE>. 


</LI>


<LI>
<CODE>mnesia:dirty_delete_object(Record)</CODE> This function is
the dirty operation alternative to the function
<CODE>delete_object/1</CODE> 


</LI>


<LI>
<CODE>mnesia:dirty_first(Tab)</CODE>. This function returns the
&#34;first&#34; key in the table <CODE>Tab</CODE>. 

Records in <CODE>set</CODE> or <CODE>bag</CODE> tables are not sorted. 
         However, there is
         a record order which is not known to the user.
         This means that it is possible to traverse a table by means of
         this function in conjunction with the <CODE>dirty_next/2</CODE>
         function.

<BR>
 If there are no records at all in the table, this function
         will return the atom <CODE>'$end_of_table'</CODE>. It is not
         recommended to use this atom as the key for any user
         records. 

<BR>

</LI>


<LI>
<CODE>mnesia:dirty_next(Tab, Key)</CODE>. This function returns
        the &#34;next&#34; key in the table <CODE>Tab</CODE>. This function makes it
        possible to traverse a table and perform some operation on all
        records in the table. When the end of the table is reached the
        special key <CODE>'$end_of_table'</CODE> is returned. Otherwise, the
        function returns a key which can be used to read the actual
        record. 
        <BR>
The behavior is undefined if any process perform a write
        operation on the table while we traverse the table with the
        <CODE>dirty_next/2</CODE> function. This is because <CODE>write</CODE>
        operations on a Mnesia table may lead to internal reorganizations
        of the table itself. This is an implementation detail, but remember
        the dirty functions are low level functions. 
        

</LI>


<LI>
<CODE>mnesia:dirty_last(Tab)</CODE> This function works exactly as
        <CODE>mnesia:dirty_first/1</CODE> but returns the last object in
        Erlang term order for the <CODE>ordered_set</CODE> table type. For
        all other table types, <CODE>mnesia:dirty_first/1</CODE> and 
        <CODE>mnesia:dirty_last/1</CODE> are synonyms.
        

</LI>


<LI>
<CODE>mnesia:dirty_prev(Tab, Key)</CODE> This function works exactly as
        <CODE>mnesia:dirty_next/2</CODE> but returns the previous object in
        Erlang term order for the ordered_set table type. For
        all other table types, <CODE>mnesia:dirty_next/2</CODE> and 
        <CODE>mnesia:dirty_prev/2</CODE> are synonyms.


</LI>


<LI>
<CODE>mnesia:dirty_slot(Tab, Slot)</CODE>

<BR>
Returns the list of records that are associated with Slot
         in a table. It can be used to traverse a table in a manner
         similar to the <CODE>dirty_next/2</CODE> function. A table has a
         number of slots that range from zero to some unknown upper
         bound. The function <CODE>dirty_slot/2</CODE> returns the special
         atom <CODE>'$end_of_table'</CODE> when the end of the table is
         reached.
         <BR>
The behavior of this function is undefined if the
         table is written on while being
         traversed. <CODE>mnesia:read_lock_table(Tab)</CODE> may be used to
         ensure that no transaction protected writes are performed
         during the iteration. 

<BR>

</LI>


<LI>
<CODE>mnesia:dirty_update_counter({Tab,Key}, Val)</CODE>. 

 Counters are positive integers with a value greater than or
         equal to zero. Updating a counter will add the <CODE> Val</CODE> and
         the counter where <CODE>Val</CODE> is a positive or negative integer.
         <BR>
 There exists no special counter records in
         Mnesia. However, records on the form of <CODE>{TabName, Key,
         Integer}</CODE> can be used as counters, and can be
         persistent. 

<BR>
It is not possible to have transaction protected updates of
counter records.

<BR>
There are two significant differences when using this
function instead of reading the record, performing the
arithmetic, and writing the record:

<BR>

<OL>

<LI>
it is much more efficient


</LI>


<LI>
the <CODE>dirty_update_counter/2</CODE> function is
performed as an atomic operation although it is not protected by
a transaction. Accordingly, no table update is lost if two
processes simultaneously execute the
<CODE>dirty_update_counter/2</CODE> function.


</LI>


</OL>
 


</LI>


<LI>
<CODE>mnesia:dirty_match_object(Pat)</CODE>. This function is
the dirty equivalent of <CODE>mnesia:match_object/1</CODE>. 


</LI>


<LI>
<CODE>mnesia:dirty_select(Tab, Pat)</CODE>. This function is
        the dirty equivalent of <CODE>mnesia:select/2</CODE>. 


</LI>


<LI>
<CODE>mnesia:dirty_index_match_object(Pat, Pos)</CODE>. This
function is the dirty equivalent of
<CODE>mnesia:index_match_object/2</CODE>. 


</LI>


<LI>
<CODE>mnesia:dirty_index_read(Tab, SecondaryKey, Pos)</CODE>. This
function is the dirty equivalent of <CODE>mnesia:index_read/3</CODE>. 


</LI>


<LI>
<CODE>mnesia:dirty_all_keys(Tab)</CODE>. This function is the
dirty equivalent of <CODE>mnesia:all_keys/1</CODE>. 


</LI>


</UL>
<A NAME="recordnames_tablenames"><!-- Empty --></A><A NAME="4.4"><!-- Empty --></A>
<H3>4.4 Record Names versus Table Names</H3>

<P>In Mnesia, all records in a table must have the same name. All
the records must be instances of the same
record type. The record name does however not necessarily be
the same as the table name. Even though that it is the case in
the most of the examples in this document. If a table is created
without the <CODE>record_name</CODE> property the code below will 
ensure all records in the tables have the same name as the table:


<PRE>
      mnesia:create_table(subscriber, [])
    
</PRE>

<P>However, if the table is is created with an explicit record name 
as argument, as shown below, it is possible to store subscriber 
records in both of the tables regardless of the table names:


<PRE>
      TabDef = [{record_name, subscriber}],
      mnesia:create_table(my_subscriber, TabDef),
      mnesia:create_table(your_subscriber, TabDef).
    
</PRE>

<P> In order to access such
tables it is not possible to use the simplified access functions
as described earlier in the document. For example, 
writing a subscriber record into a table requires a
<CODE>mnesia:write/3</CODE>function instead of the simplified functions
<CODE>mnesia:write/1</CODE> and <CODE>mnesia:s_write/1</CODE>:


<PRE>
      mnesia:write(subscriber, #subscriber{}, write)
      mnesia:write(my_subscriber, #subscriber{}, sticky_write)
      mnesia:write(your_subscriber, #subscriber{}, write)
    
</PRE>

<P>The following simplified piece of code illustrates the
relationship between the simplified access functions used in
most examples and their more flexible counterparts:


<PRE>
      mnesia:dirty_write(Record) -&#62;
        Tab = element(1, Record),
        mnesia:dirty_write(Tab, Record).
      
      mnesia:dirty_delete({Tab, Key}) -&#62;
        mnesia:dirty_delete(Tab, Key).
      
      mnesia:dirty_delete_object(Record) -&#62;
        Tab = element(1, Record),
        mnesia:dirty_delete_object(Tab, Record) 
      
      mnesia:dirty_update_counter({Tab, Key}, Incr) -&#62;
        mnesia:dirty_update_counter(Tab, Key, Incr).
      
      mnesia:dirty_read({Tab, Key}) -&#62;
        Tab = element(1, Record),
        mnesia:dirty_read(Tab, Key).
      
      mnesia:dirty_match_object(Pattern) -&#62;
        Tab = element(1, Pattern),
        mnesia:dirty_match_object(Tab, Pattern).
      
      mnesia:dirty_index_match_object(Pattern, Attr) 
        Tab = element(1, Pattern),
        mnesia:dirty_index_match_object(Tab, Pattern, Attr).
      
      mnesia:write(Record) -&#62;
        Tab = element(1, Record),
        mnesia:write(Tab, Record, write).
      
      mnesia:s_write(Record) -&#62;
        Tab = element(1, Record),
        mnesia:write(Tab, Record, sticky_write).
      
      mnesia:delete({Tab, Key}) -&#62;
        mnesia:delete(Tab, Key, write).
      
      mnesia:s_delete({Tab, Key}) -&#62;
        mnesia:delete(Tab, Key, sticky_write).
      
      mnesia:delete_object(Record) -&#62;
        Tab = element(1, Record),
        mnesia:delete_object(Tab, Record, write).
      
      mnesia:s_delete_object(Record) -&#62;
        Tab = element(1, Record),
        mnesia:delete_object(Tab, Record. sticky_write).
      
      mnesia:read({Tab, Key}) -&#62;
        mnesia:read(Tab, Key, read).
      
      mnesia:wread({Tab, Key}) -&#62;
        mnesia:read(Tab, Key, write).
      
      mnesia:match_object(Pattern) -&#62;
        Tab = element(1, Pattern),
        mnesia:match_object(Tab, Pattern, read).
      
      mnesia:index_match_object(Pattern, Attr) -&#62;
        Tab = element(1, Pattern),
        mnesia:index_match_object(Tab, Pattern, Attr, read).
    
</PRE>
<A NAME="4.5"><!-- Empty --></A>
<H3>4.5 Activity Concept and Various Access Contexts</H3>

<P>As previously described, a functional object (Fun) performing
table access operations as listed below may be
passed on as arguments to the function
<CODE>mnesia:transaction/1,2,3</CODE>: 


<P>
<UL>

<LI>
mnesia:write/3 (write/1, s_write/1)
<BR>

</LI>


<LI>
mnesia:delete/3 (delete/1, s_delete/1)
<BR>

</LI>


<LI>
mnesia:delete_object/3 (delete_object/1, s_delete_object/1)
<BR>

</LI>


<LI>
mnesia:read/3 (read/1, wread/1)
<BR>

</LI>


<LI>
mnesia:match_object/2 (match_object/1)
<BR>

</LI>


<LI>
mnesia:select/3 (select/2)
<BR>

</LI>


<LI>
mnesia:foldl/3 (foldl/4, foldr/3, foldr/4)
<BR>

</LI>


<LI>
mnesia:all_keys/1
<BR>

</LI>


<LI>
mnesia:index_match_object/4 (index_match_object/2)
<BR>

</LI>


<LI>
mnesia:index_read/3
<BR>

</LI>


<LI>
mnesia:lock/2 (read_lock_table/1, write_lock_table/1)
<BR>

</LI>


<LI>
mnesia:table_info/2
<BR>

</LI>


</UL>

<P>These functions will be performed in a
transaction context involving mechanisms like locking, logging,
replication, checkpoints, subscriptions, commit protocols
etc.However, the same function may also be
evaluated in other activity contexts. 
<BR>
The following activity access contexts are currently supported:


<P>
<UL>

<LI>
transaction 
<BR>

</LI>


<LI>
sync_transaction
<BR>

</LI>


<LI>
async_dirty
<BR>

</LI>


<LI>
sync_dirty
<BR>

</LI>


<LI>
ets
<BR>

</LI>


</UL>

<P>By passing the same &#34;fun&#34; as argument to the function
<CODE>mnesia:sync_transaction(Fun [, Args])</CODE> it will be performed
in synced transaction context. Synced transactions waits until all
active replicas has committed the transaction (to disc) before
returning from the mnesia:sync_transaction call. Using
sync_transaction is useful for applications that are executing on
several nodes and want to be sure that the update is performed on
the remote nodes before a remote process is spawned or a message
is sent to a remote process, and also when combining transaction
writes with dirty_reads. This is also useful in situations where
an application performs frequent or voluminous updates which may
overload Mnesia on other nodes.



<P>By passing the same &#34;fun&#34; as argument to the function
<CODE>mnesia:async_dirty(Fun [, Args])</CODE> it will be performed in
dirty context. The function calls will be mapped to the
corresponding dirty functions. This will still involve logging,
replication and subscriptions but there will be no locking,
local transaction storage or commit protocols involved.
Checkpoint retainers will be updated but will be updated
&#34;dirty&#34;. Thus, they will be updated asynchronously. The
functions will wait for the operation to be performed on one
node but not the others. If the table resides locally no waiting
will occur.


<P>By passing the same &#34;fun&#34; as an argument to the function
<CODE>mnesia:sync_dirty(Fun [, Args])</CODE> it will be performed in
almost the same context as <CODE>mnesia:async_dirty/1,2</CODE>. The
difference is that the operations are performed
synchronously. The caller will wait for the updates to be
performed on all active replicas. Using sync_dirty is useful for
applications that are executing on several nodes and want to be
sure that the update is performed on the remote nodes before a remote
process is spawned or a message is sent to a remote process. This
is also useful in situations where an application performs frequent or
voluminous updates which may overload Mnesia on other
nodes.


<P>Mnesia tables with storage type RAM_copies and disc_copies
are implemented internally as &#34;ets-tables&#34; and 
it is possible for applications to access the these tables
directly. This is only recommended if all options have been weighed
and the possible outcomes are understood. By passing the earlier 
mentioned &#34;fun&#34; to the function
<CODE>mnesia:ets(Fun [, Args])</CODE> it will be performed but in a very raw
context. The operations will be performed directly on the
local ets tables assuming that the local storage type are
RAM_copies and that the table is not replicated on other
nodes. Subscriptions will not be triggered nor
checkpoints updated, but this operation is blindingly fast. Disc resident
tables should not be updated with the ets-function since the
disc will not be updated.


<P>The Fun may also be passed as an argument to the function
<CODE>mnesia:activity/2,3,4</CODE> which enables usage of customized
activity access callback modules. It can either be obtained
directly by stating the module name as argument or implicitly
by usage of the <CODE>access_module</CODE> configuration parameter. A
customized callback module may be used for several purposes,
such as providing triggers, integrity constraints, run time
statistics, or virtual tables.
<BR>
 The callback module does
not have to access real Mnesia tables, it is free to do whatever
it likes as long as the callback interface is fulfilled.
<BR>
 In Appendix C &#34;The Activity Access Call Back Interface&#34; the source
code for one alternate implementation is provided
(mnesia_frag.erl). The context sensitive function
<CODE>mnesia:table_info/2</CODE> may be used to provide virtual
information about a table. One usage of this is to perform
<CODE>QLC</CODE> queries within an activity context with a
customized callback module. By providing table information about
table indices and other <CODE>QLC</CODE> requirements,
<CODE>QLC</CODE> may be used as a generic query language to
access virtual tables.


<P>QLC queries may be performed in all these activity
contexts (transaction, sync_transaction, async_dirty, sync_dirty
and ets). The ets activity will only work if the table has no
indices.


<P>
<TABLE CELLPADDING=4>
  <TR>
    <TD VALIGN=TOP><IMG ALT="Note!" SRC="note.gif"></TD>
    <TD>

<P> The mnesia:dirty_* function always executes with
async_dirty semantics regardless of which activity access contexts
are invoked. They may even invoke contexts without any
enclosing activity access context.
    </TD>
  </TR>
</TABLE>
<A NAME="4.6"><!-- Empty --></A>
<H3>4.6 Nested transactions</H3>

<P>Transactions may be nested in an arbitrary fashion. A child transaction
must run in the same process as its parent. When a child transaction
aborts, the caller of the child transaction will get the 
return value <CODE>{aborted, Reason}</CODE> and any work performed
by the child will be erased. If a child transaction commits, the
records written by the child will be propagated to the parent.


<P>No locks are released when child transactions terminate. Locks
created by a sequence of nested transactions are kept until 
the topmost transaction terminates. Furthermore, any updates 
performed by a nested transaction are only propagated 
in such a manner so that the parent of the nested transaction
sees the updates. No final commitment will be done until
the top level transaction is terminated.
So, although a nested transaction returns <CODE>{atomic, Val}</CODE>,
if the enclosing parent transaction is aborted, the entire
nested operation is aborted.


<P>The ability to have nested transaction with identical semantics
as top level transaction makes it easier to write
library functions that manipulate mnesia tables.


<P>Say for example that we have a function that adds a
new subscriber to a telephony system:

<PRE>
      add_subscriber(S) -&#62;
          mnesia:transaction(fun() -&#62;
              case mnesia:read( ..........
    
</PRE>

<P>This function needs to be called as a transaction.
Now assume that we wish to write a function that
both calls the <CODE>add_subscriber/1</CODE> function and
is in itself protected by the context of a transaction.
By simply calling the <CODE>add_subscriber/1</CODE> from within
another transaction, a nested transaction is created.


<P>It is also possible to mix different activity access contexts while nesting, 
but the dirty ones (async_dirty,sync_dirty and ets) will inherit the transaction
semantics if they are called inside a transaction and thus it will grab locks and 
use two or three phase commit.


<PRE>
      add_subscriber(S) -&#62;
          mnesia:transaction(fun() -&#62;
             %% Transaction context 
             mnesia:read({some_tab, some_data}),
             mnesia:sync_dirty(fun() -&#62;
                 %% Still in a transaction context.
                 case mnesia:read( ..) ..end), end).
      add_subscriber2(S) -&#62;
          mnesia:sync_dirty(fun() -&#62;
             %% In dirty context 
             mnesia:read({some_tab, some_data}),
             mnesia:transaction(fun() -&#62;
                 %% In a transaction context.
                 case mnesia:read( ..) ..end), end).
    
</PRE>
<A NAME="4.7"><!-- Empty --></A>
<H3>4.7 Pattern Matching</H3>
<A NAME="matching"><!-- Empty --></A>
<P>When it is not possible to use <CODE>mnesia:read/3</CODE> Mnesia
provides the programmer with several functions for matching
records against a pattern. The most useful functions of these are:


<PRE>
      mnesia:select(Tab, MatchSpecification, LockKind) -&#62;
          transaction abort | [ObjectList]
      mnesia:select(Tab, MatchSpecification, NObjects, Lock) -&#62;  
          transaction abort | {[Object],Continuation} | '$end_of_table'
      mnesia:select(Cont) -&#62;
          transaction abort | {[Object],Continuation} | '$end_of_table'
      mnesia:match_object(Tab, Pattern, LockKind) -&#62;
          transaction abort | RecordList
    
</PRE>

<P>These functions matches a <CODE>Pattern</CODE> against all records in
table <CODE>Tab</CODE>. In a <CODE>mnesia:select</CODE> call <CODE>Pattern</CODE> is
a part of <CODE>MatchSpecification</CODE> described below. It is not
necessarily performed as an exhaustive search of the entire
table. By utilizing indices and bound values in the key of the
pattern, the actual work done by the function may be condensed
into a few hash lookups. Using <CODE>ordered_set</CODE> tables may reduce the
search space if the keys are partially bound.


<P>The pattern provided to the functions must be a valid record,
and the first element of the provided tuple must be the
<CODE>record_name</CODE> of the table. The special element <CODE>'_'</CODE>
matches any data structure in Erlang (also known as an Erlang
term). The special elements <CODE>'$&#60;number&#62;'</CODE> behaves as Erlang
variables i.e. matches anything and binds the first occurrence and
matches the coming occurrences of that variable against the bound value.


<P>Use the function <CODE>mnesia:table_info(Tab, wild_pattern)</CODE> 
to obtain a basic pattern which matches all records in a table 
or use the default value in record creation.
Do not make the pattern hard coded since it will make your code more
vulnerable to future changes of the record definition.


<PRE>
      Wildpattern = mnesia:table_info(employee, wild_pattern), 
      %% Or use
      Wildpattern = #employee{_ = '_'},
    
</PRE>

<P>For the employee table the wild pattern will look like:

<PRE>
      {employee, '_', '_', '_', '_', '_',' _'}.
    
</PRE>

<P>In order to constrain the match you must replace some
of the <CODE>'_'</CODE> elements. The code for matching out
all female employees, looks like:


<PRE>
      Pat = #employee{sex = female, _ = '_'},
      F = fun() -&#62; mnesia:match_object(Pat) end,
      Females = mnesia:transaction(F).
    
</PRE>

<P>It is also possible to use the match function if we want to
check the equality of different attributes. Assume that we want
to find all employees which happens to have a employee number
which is equal to their room number:


<PRE>
      Pat = #employee{emp_no = '$1', room_no = '$1', _ = '_'},
      F = fun() -&#62; mnesia:match_object(Pat) end,
      Odd = mnesia:transaction(F).
    
</PRE>

<P> The function <CODE>mnesia:match_object/3</CODE> lacks some important
features that <CODE>mnesia:select/3</CODE> have. For example
<CODE>mnesia:match_object/3</CODE> can only return the matching records,
and it can not express constraints other then equality.
If we want to find the names of the male employees on the second floor
we could write:


<PRE>
      MatchHead = #employee{name='$1', sex=male, room_no={'$2', '_'}, _='_'},
      Guard = [{'&#62;=', '$2', 220},{'&#60;', '$2', 230}],
      Result = '$1',
      mnesia:select(employee,[{MatchHead, Guard, [Result]}])

</PRE>

<P> Select can be used to add additional constraints and create
output which can not be done with <CODE>mnesia:match_object/3</CODE>. 

<P> The second argument to select is a <CODE>MatchSpecification</CODE>.
A <CODE>MatchSpecification</CODE> is list of <CODE>MatchFunctions</CODE>, where
each <CODE>MatchFunction</CODE> consists of a tuple containing
<CODE>{MatchHead, MatchCondition, MatchBody}</CODE>. <CODE>MatchHead</CODE>
is the same pattern used in <CODE>mnesia:match_object/3</CODE> 
described above. <CODE>MatchCondition</CODE> is a list of additional
constraints applied to each record, and <CODE>MatchBody</CODE> is used 
to construct the return values.


<P> A detailed explanation of match specifications can be found in 
the <STRONG>Erts users guide: Match specifications in Erlang </STRONG>,
and the ets/dets documentations may provide some additional 
information.


<P> The functions <CODE>select/4</CODE> and <CODE>select/1</CODE> are used to
get a limited number of results, where the <CODE>Continuation</CODE>
are used to get the next chunk of results. Mnesia uses the
<CODE>NObjects</CODE> as an recommendation only, thus more or less
results then specified with <CODE>NObjects</CODE> may be returned in
the result list, even the empty list may be returned despite there
are more results to collect.


<P>
<TABLE CELLPADDING=4>
  <TR>
    <TD VALIGN=TOP><IMG ALT="Warning!" SRC="warning.gif"></TD>
    <TD>

<P>There is a severe performance penalty in using
        <CODE>mnesia:select/[1|2|3|4]</CODE> after any modifying operations
        are done on that table in the same transaction, i.e. avoid using
        <CODE>mnesia:write/1</CODE> or <CODE>mnesia:delete/1</CODE> before a
        <CODE>mnesia:select</CODE> in the same transaction.
    </TD>
  </TR>
</TABLE>

<P>If the key attribute is bound in a pattern, the match operation
is very efficient. However, if the key attribute in a pattern is
given as <CODE>'_'</CODE>, or <CODE>'$1'</CODE>, the whole <CODE>employee</CODE>
table must be searched for records that match. Hence if the table is
large, this can become a time consuming operation, but it can be
remedied with indices (refer to Chapter 5: <A HREF="Mnesia_chap5.html#indexing">Indexing</A>) if
<CODE>mnesia:match_object</CODE> is used.


<P> QLC queries can also be used to search Mnesia tables. By
using <CODE>mnesia:table/[1|2]</CODE> as the generator inside a QLC
query you let the query operate on a mnesia table. Mnesia
specific options to <CODE>mnesia:table/2</CODE> are {lock, Lock},
{n_objects,Integer} and {traverse, SelMethod}. The <CODE>lock</CODE>
option specifies whether mnesia should acquire a read or write
lock on the table, and <CODE>n_objects</CODE> specifies how many
results should be returned in each chunk to QLC. The last option is
<CODE>traverse</CODE> and it specifies which function mnesia should
use to traverse the table. Default <CODE>select</CODE> is used, but by using
<CODE>{traverse, {select, MatchSpecification}}</CODE> as an option to
<CODE>mnesia:table/2</CODE> the user can specify it's own view of the
table.


<P> If no options are specified a read lock will acquired and 100
results will be returned in each chunk, and select will be used
to traverse the table, i.e.:


<PRE>
      mnesia:table(Tab) -&#62;
          mnesia:table(Tab, [{n_objects,100},{lock, read}, {traverse, select}]).
    
</PRE>

<P>The function <CODE>mnesia:all_keys(Tab)</CODE> returns all keys in a
table.
<A NAME="4.8"><!-- Empty --></A>
<H3>4.8 Iteration</H3>
<A NAME="iteration"><!-- Empty --></A>
<P>Mnesia provides a couple of functions which iterates over all
the records in a table. 


<PRE>
      mnesia:foldl(Fun, Acc0, Tab) -&#62; NewAcc | transaction abort
      mnesia:foldr(Fun, Acc0, Tab) -&#62; NewAcc | transaction abort
      mnesia:foldl(Fun, Acc0, Tab, LockType) -&#62; NewAcc | transaction abort
      mnesia:foldr(Fun, Acc0, Tab, LockType) -&#62; NewAcc | transaction abort
    
</PRE>

<P>These functions iterate over the mnesia table <CODE>Tab</CODE> and
apply the function <CODE>Fun</CODE> to each record. The <CODE>Fun</CODE>
takes two arguments, the first argument is a record from the
table and the second argument is the accumulator. The
<CODE>Fun</CODE> return a new accumulator. 

<P>The first time the <CODE>Fun</CODE> is applied <CODE>Acc0</CODE> will
be the second argument. The next time the <CODE>Fun</CODE> is called
the return value from the previous call, will be used as the 
second argument. The term the last call to the Fun returns
will be the return value of the <CODE>fold[lr]</CODE> function.


<P>The difference between <CODE>foldl</CODE> and <CODE>foldr</CODE> is the 
order the table is accessed for <CODE>ordered_set</CODE> tables,
for every other table type the functions are equivalent.


<P><CODE>LockType</CODE> specifies what type of lock that shall be 
acquired for the iteration, default is <CODE>read</CODE>. If
records are written or deleted during the iteration a write 
lock should be acquired. 

<P> These functions might be used to find records in a table
when it is impossible to write constraints for
<CODE>mnesia:match_object/3</CODE>, or when you want to perform 
some action on certain records. 


<P> For example finding all the employees who has a salary 
below 10 could look like:

<PRE>
      find_low_salaries() -&#62;
        Constraint = 
             fun(Emp, Acc) when Emp#employee.salary &#60; 10 -&#62;
                    [Emp | Acc];
                (_, Acc) -&#62;
                    Acc
             end,
        Find = fun() -&#62; mnesia:foldl(Constraint, [], employee) end,
        mnesia:transaction(Find).
    
</PRE>

<P> Raising the salary to 10 for everyone with a salary below 10
and return the sum of all raises:

<PRE>
      increase_low_salaries() -&#62;
         Increase = 
             fun(Emp, Acc) when Emp#employee.salary &#60; 10 -&#62;
                    OldS = Emp#employee.salary,
                    ok = mnesia:write(Emp#employee{salary = 10}),
                    Acc + 10 - OldS;
                (_, Acc) -&#62;
                    Acc
             end,
        IncLow = fun() -&#62; mnesia:foldl(Increase, 0, employee, write) end,
        mnesia:transaction(IncLow).
    
</PRE>

<P> A lot of nice things can be done with the iterator functions
but some caution should be taken about performance and memory
utilization for large tables. 

<P>Call these iteration functions on nodes that contain a replica of the
table. Each call to the function <CODE>Fun</CODE> access the table and if the table
resides on another node it will generate a lot of unnecessary
network traffic. 

<P>Mnesia also provides some functions that make it possible for
the user to iterate over the table. The order of the
iteration is unspecified if the table is not of the <CODE>ordered_set</CODE> 
type. 

<PRE>
      mnesia:first(Tab) -&#62;  Key | transaction abort
      mnesia:last(Tab)  -&#62;  Key | transaction abort
      mnesia:next(Tab,Key)  -&#62;  Key | transaction abort
      mnesia:prev(Tab,Key)  -&#62;  Key | transaction abort
    
</PRE>

<P>The order of first/last and next/prev are only valid for
<CODE>ordered_set</CODE> tables, for all other tables, they are synonyms.
When the end of the table is reached the special key
<CODE>'$end_of_table'</CODE> is returned.

<P> If records are written and deleted during the traversal, use
<CODE>mnesia:fold[lr]/4</CODE> with a <CODE>write</CODE> lock. Or
<CODE>mnesia:write_lock_table/1</CODE> when using first and next.

<P> Writing or deleting in transaction context creates a local copy
of each modified record, so modifying each record in a large
table uses a lot of memory. Mnesia will compensate for every
written or deleted record during the iteration in a transaction
context, which may reduce the performance. If possible avoid writing 
or deleting records in the same transaction before iterating over the
table.

<P> In dirty context, i.e. <CODE>sync_dirty</CODE> or <CODE>async_dirty</CODE>,
the modified records are not stored in a local copy; instead,
each record is updated separately. This generates a lot of
network traffic if the table has a replica on another node and
has all the other drawbacks that dirty operations
have. Especially for the <CODE>mnesia:first/1</CODE> and
<CODE>mnesia:next/2</CODE> commands, the same drawbacks as described
above for <CODE>dirty_first</CODE> and <CODE>dirty_next</CODE> applies, i.e. 
no writes to the table should be done during iteration.

<P> <CENTER>
<HR>
<SMALL>
Copyright &copy; 1991-2006
<A HREF="http://www.erlang.se">Ericsson AB</A><BR>
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