Performing Transactions

Overview

To enable transactional support for a specific cache, set the atomicityMode parameter in the cache configuration to TRANSACTIONAL. See Atomicity Modes for details.

Transactions allow you to group multiple cache operations, on one or more keys, into a single atomic transaction. These operations are executed without any other interleaved operations on the specified keys, and either all succeed or all fail. There is no partial execution of the operations.

You can enable transactions for a specific cache in the cache configuration.

<bean class="org.apache.ignite.configuration.IgniteConfiguration">

    <property name="transactionConfiguration">
        <bean class="org.apache.ignite.configuration.TransactionConfiguration">
            <!--Set the timeout to 20 seconds-->
            <property name="TxTimeoutOnPartitionMapExchange" value="20000"/>
        </bean>
    </property>

</bean>

CacheConfiguration cacheCfg = new CacheConfiguration();

cacheCfg.setName("cacheName");

cacheCfg.setAtomicityMode(CacheAtomicityMode.TRANSACTIONAL);

IgniteConfiguration cfg = new IgniteConfiguration();

cfg = Util.getIgniteCfg();
cfg.setCacheConfiguration(cacheCfg);

// Create a Transaction configuration
TransactionConfiguration txCfg = new TransactionConfiguration();

// Set the timeout to 20 seconds
txCfg.setTxTimeoutOnPartitionMapExchange(20000);

cfg.setTransactionConfiguration(txCfg);

// Start the node
Ignition.start(cfg);

var cfg = new IgniteConfiguration
{
    CacheConfiguration = new[]
    {
        new CacheConfiguration("txCache")
        {
            AtomicityMode = CacheAtomicityMode.Transactional
        }
    },
    TransactionConfiguration = new TransactionConfiguration
    {
        DefaultTimeoutOnPartitionMapExchange = TimeSpan.FromSeconds(20)
    }
};

This API is not presently available for C++. You can use XML configuration.

Executing Transactions

The key-value API provides an interface for starting and completing transactions as well as getting transaction-related metrics. The interface can be obtained from an instance of Ignite.

Ignite ignite = Ignition.ignite();

IgniteTransactions transactions = ignite.transactions();

try (Transaction tx = transactions.txStart()) {
    Integer hello = cache.get("Hello");

    if (hello == 1)
        cache.put("Hello", 11);

    cache.put("World", 22);

    tx.commit();
}

var cfg = new IgniteConfiguration
{
    DiscoverySpi = new TcpDiscoverySpi
    {
        LocalPort = 48500,
        LocalPortRange = 20,
        IpFinder = new TcpDiscoveryStaticIpFinder
        {
            Endpoints = new[]
            {
                "127.0.0.1:48500..48520"
            }
        }
    },
    CacheConfiguration = new[]
    {
        new CacheConfiguration
        {
            Name = "cacheName",
            AtomicityMode = CacheAtomicityMode.Transactional
        }
    },
    TransactionConfiguration = new TransactionConfiguration
    {
        DefaultTimeoutOnPartitionMapExchange = TimeSpan.FromSeconds(20)
    }
};

var ignite = Ignition.Start(cfg);
var cache = ignite.GetCache<string, int>("cacheName");
cache.Put("Hello", 1);
var transactions = ignite.GetTransactions();

using (var tx = transactions.TxStart())
{
    int hello = cache.Get("Hello");

    if (hello == 1)
    {
        cache.Put("Hello", 11);
    }

    cache.Put("World", 22);

    tx.Commit();
}

Transactions transactions = ignite.GetTransactions();

Transaction tx = transactions.TxStart();
int hello = cache.Get("Hello");

if (hello == 1)
    cache.Put("Hello", 11);

cache.Put("World", 22);

tx.Commit();

Concurrency Modes and Isolation Levels

Caches with the TRANSACTIONAL atomicity mode support both OPTIMISTIC and PESSIMISTIC concurrency modes for transactions. Concurrency mode determines when an entry-level transaction lock is acquired: at the time of data access or during the prepare phase. Locking prevents concurrent access to an object. For example, when you attempt to update a ToDo list item with pessimistic locking, the server places a lock on the object until you either commit or rollback the transaction and no other transaction or operation is allowed to update the same entry. Regardless of the concurrency mode used in a transaction, there exists a moment in time when all entries enlisted in the transaction are locked before the commit.

Isolation level defines how concurrent transactions 'see' and handle operations on the same keys. Ignite supports READ_COMMITTED, REPEATABLE_READ and SERIALIZABLE isolation levels.

All combinations of concurrency modes and isolation levels are allowed. Below is the description of the system behavior and the guarantees provided by each concurrency-isolation combination.

Pessimistic Transactions

In PESSIMISTIC transactions, locks are acquired during the first read or write access (depending on the isolation level) and held by the transaction until it is committed or rolled back. In this mode locks are acquired on primary nodes first and then promoted to backup nodes during the prepare stage. The following isolation levels can be configured with the PESSIMISTIC concurrency mode:

READ_COMMITTED - Data is read without a lock and is never cached in the transaction itself. The data may be read from a backup node if this is allowed in the cache configuration. In this isolation mode you can have the so-called Non-Repeatable Reads
because a concurrent transaction can change the data when you are reading the data twice in your transaction. The lock is only acquired at the time of first write access (this includes EntryProcessor invocation). This means that an entry that has been read during the transaction may have a different value by the time the transaction is committed. No exception is thrown in this case.
REPEATABLE_READ - Entry lock is acquired and data is fetched from the primary node on the first read or write access and stored in the local transactional map. All consecutive access to the same data is local and returns the last read or updated transaction value. This means no other concurrent transactions can make changes to the locked data, and you are getting Repeatable Reads for your transaction.
SERIALIZABLE - In the PESSIMISTIC mode, this isolation level works the same way as REPEATABLE_READ.

Note that in the PESSIMISTIC mode, the order of locking is important. Moreover, locks are acquired sequentially and exactly in the specified order.

Optimistic Transactions

In OPTIMISTIC transactions, entry locks are acquired on primary nodes during the first phase of 2PC, at the prepare step, and then promoted to backup nodes and released once the transaction is committed. The locks are never acquired if you roll back the transaction and no commit attempt was made. The following isolation levels can be configured with the OPTIMISTIC concurrency mode:

READ_COMMITTED - Changes that should be applied to the cache are collected on the originating node and applied upon the transaction commit. Transaction data is read without a lock and is never cached in the transaction. The data may be read from a backup node if this is allowed in the cache configuration. In this isolation you can have so-called Non-Repeatable Reads because a concurrent transaction can change the data when you are reading the data twice in your transaction. This mode combination does not check if the entry value has been modified since the first read or write access and never raises an optimistic exception.
REPEATABLE_READ - Transactions at this isolation level work similar to OPTIMISTIC READ_COMMITTED transactions with only one difference: read values are cached on the originating node and all subsequent reads are guaranteed to be local. This mode combination does not check if the entry value has been modified since the first read or write access and never raises an optimistic exception.
SERIALIZABLE - Stores an entry version upon first read access. Ignite fails a transaction at the commit stage if the Ignite engine detects that at least one of the entries used as part of the initiated transaction has been modified. In short, this means that if Ignite detects that there is a conflict at the commit stage of a transaction, it fails the transaction, throwing TransactionOptimisticException and rolling back any changes made. Make sure you handle this exception and retry the transaction.

CacheConfiguration<Integer, String> cfg = new CacheConfiguration<>();
cfg.setAtomicityMode(CacheAtomicityMode.TRANSACTIONAL);
cfg.setName("myCache");
IgniteCache<Integer, String> cache = ignite.getOrCreateCache(cfg);

// Re-try the transaction a limited number of times.
int retryCount = 10;
int retries = 0;

// Start a transaction in the optimistic mode with the serializable isolation
// level.
while (retries < retryCount) {
    retries++;
    try (Transaction tx = ignite.transactions().txStart(TransactionConcurrency.OPTIMISTIC,
            TransactionIsolation.SERIALIZABLE)) {
        // modify cache entries as part of this transaction.
        cache.put(1, "foo");
        cache.put(2, "bar");
        // commit the transaction
        tx.commit();

        // the transaction succeeded. Leave the while loop.
        break;
    } catch (TransactionOptimisticException e) {
        // Transaction has failed. Retry.
    }
}

var cfg = new IgniteConfiguration
{
    DiscoverySpi = new TcpDiscoverySpi
    {
        LocalPort = 48500,
        LocalPortRange = 20,
        IpFinder = new TcpDiscoveryStaticIpFinder
        {
            Endpoints = new[]
            {
                "127.0.0.1:48500..48520"
            }
        }
    },
    CacheConfiguration = new[]
    {
        new CacheConfiguration
        {
            Name = "cacheName",
            AtomicityMode = CacheAtomicityMode.Transactional
        }
    },
    TransactionConfiguration = new TransactionConfiguration
    {
        DefaultTimeoutOnPartitionMapExchange = TimeSpan.FromSeconds(20)
    }
};

var ignite = Ignition.Start(cfg);
// Re-try the transaction a limited number of times
var retryCount = 10;
var retries = 0;

// Start a transaction in the optimistic mode with the serializable isolation level
while (retries < retryCount)
{
    retries++;
    try
    {
        using (var tx = ignite.GetTransactions().TxStart(TransactionConcurrency.Optimistic,
            TransactionIsolation.Serializable))
        {
            // modify cache entries as part of this transaction.

            // commit the transaction
            tx.Commit();

            // the transaction succeeded. Leave the while loop.
            break;
        }
    }
    catch (TransactionOptimisticException)
    {
        // Transaction has failed. Retry.
    }

}

// Re-try the transaction a limited number of times.
int const retryCount = 10;
int retries = 0;

// Start a transaction in the optimistic mode with the serializable isolation level.
while (retries < retryCount)
{
    retries++;

    try
    {
        Transaction tx = ignite.GetTransactions().TxStart(
                TransactionConcurrency::OPTIMISTIC, TransactionIsolation::SERIALIZABLE);

        // commit the transaction
        tx.Commit();

        // the transaction succeeded. Leave the while loop.
        break;
    }
    catch (IgniteError e)
    {
        // Transaction has failed. Retry.
    }
}

Another important point to note here is that a transaction fails even if an entry was read without being modified (cache.put(…)), since the value of the entry could be important to the logic within the initiated transaction.

Note that the key order is important for READ_COMMITTED and REPEATABLE_READ transactions since the locks are still acquired sequentially in these modes.

Read Consistency

In order to achieve full read consistency in PESSIMISTIC mode, read-locks need to be acquired. This means that full consistency between reads in the PESSIMISTIC mode can be achieved only with PESSIMISTIC REPEATABLE_READ (or SERIALIZABLE) transactions.

When using OPTIMISTIC transactions, full read consistency can be achieved by disallowing potential conflicts between reads. This behavior is provided by OPTIMISTIC SERIALIZABLE mode. Note, however, that until the commit happens you can still read a partial transaction state, so the transaction logic must protect against it. Only during the commit phase, in case of any conflict, a TransactionOptimisticException is thrown allowing you to retry the transaction.

Deadlock Detection

One major rule that you must follow when working with distributed transactions is that locks for the keys participating in a transaction must be acquired in the same order. Violating this rule can lead to a distributed deadlock.

GridGain does not avoid distributed deadlocks, but rather has built-in functionality that makes it easier to debug and fix such situations.

In the code snippet below, a transaction has been started with a timeout. If the timeout expires, the deadlock detection procedure tries to find a possible deadlock that might have caused the timeout. When the timeout expires, TransactionTimeoutException is generated and propagated to the application code as the cause of CacheException regardless of a deadlock. However, if a deadlock is detected, the cause of the returned TransactionTimeoutException will be TransactionDeadlockException (at least for one transaction involved in the deadlock).

CacheConfiguration<Integer, String> cfg = new CacheConfiguration<>();
cfg.setAtomicityMode(CacheAtomicityMode.TRANSACTIONAL);
cfg.setName("myCache");
IgniteCache<Integer, String> cache = ignite.getOrCreateCache(cfg);

try (Transaction tx = ignite.transactions().txStart(TransactionConcurrency.PESSIMISTIC,
        TransactionIsolation.READ_COMMITTED, 300, 0)) {
    cache.put(1, "1");
    cache.put(2, "1");

    tx.commit();
} catch (CacheException e) {
    if (e.getCause() instanceof TransactionTimeoutException
            && e.getCause().getCause() instanceof TransactionDeadlockException)

        System.out.println(e.getCause().getCause().getMessage());
}

var cfg = new IgniteConfiguration
{
    DiscoverySpi = new TcpDiscoverySpi
    {
        LocalPort = 48500,
        LocalPortRange = 20,
        IpFinder = new TcpDiscoveryStaticIpFinder
        {
            Endpoints = new[]
            {
                "127.0.0.1:48500..48520"
            }
        }
    },
    CacheConfiguration = new[]
    {
        new CacheConfiguration
        {
            Name = "cacheName",
            AtomicityMode = CacheAtomicityMode.Transactional
        }
    },
    TransactionConfiguration = new TransactionConfiguration
    {
        DefaultTimeoutOnPartitionMapExchange = TimeSpan.FromSeconds(20)
    }
};

var ignite = Ignition.Start(cfg);
var intCache = ignite.GetOrCreateCache<int, int>("intCache");
try
{
    using (var tx = ignite.GetTransactions().TxStart(TransactionConcurrency.Pessimistic,
        TransactionIsolation.ReadCommitted, TimeSpan.FromMilliseconds(300), 0))
    {
        intCache.Put(1, 1);
        intCache.Put(2, 1);
        tx.Commit();
    }
}
catch (TransactionTimeoutException e)
{
    Console.WriteLine(e.Message);
}
catch (TransactionDeadlockException e)
{
    Console.WriteLine(e.Message);
}

try {
    Transaction tx = ignite.GetTransactions().TxStart(
        TransactionConcurrency::PESSIMISTIC, TransactionIsolation::READ_COMMITTED, 300, 0);
    cache.Put(1, 1);

    cache.Put(2, 1);

    tx.Commit();
}
catch (IgniteError& err)
{
    std::cout << "An error occurred: " << err.GetText() << std::endl;
    std::cin.get();
    return err.GetCode();
}

The TransactionDeadlockException message contains useful information that can help you find the reason for the deadlock.

Deadlock detected:

K1: TX1 holds lock, TX2 waits lock.
K2: TX2 holds lock, TX1 waits lock.

Transactions:

TX1 [txId=GridCacheVersion [topVer=74949328, time=1463469328421, order=1463469326211, nodeOrder=1], nodeId=ad68354d-07b8-4be5-85bb-f5f2362fbb88, threadId=73]
TX2 [txId=GridCacheVersion [topVer=74949328, time=1463469328421, order=1463469326210, nodeOrder=1], nodeId=ad68354d-07b8-4be5-85bb-f5f2362fbb88, threadId=74]

Keys:

K1 [key=1, cache=default]
K2 [key=2, cache=default]

Deadlock detection is a multi-step procedure that can take many iterations depending on the number of nodes in the cluster, keys, and transactions that are involved in a possible deadlock. A deadlock detection initiator is a node where a transaction was started and failed with a TransactionTimeoutException. This node investigates if a deadlock has occurred by exchanging requests/responses with other remote nodes, and then prepares a deadlock related report that is provided with the TransactionDeadlockException. Each such message (request/response) is known as an iteration.

Since a transaction is not rolled back until the deadlock detection procedure is completed, it sometimes makes sense to tune the parameters (shown below), if you want to have a predictable time for a transaction’s rollback.

IGNITE_TX_DEADLOCK_DETECTION_MAX_ITERS - Specifies the maximum number of iterations for the deadlock detection procedure. If the value of this property is less than or equal to zero, deadlock detection is disabled (1000 by default);
IGNITE_TX_DEADLOCK_DETECTION_TIMEOUT - Specifies the timeout for the deadlock detection mechanism (1 minute by default).

Note that if there are too few iterations, you may get an incomplete deadlock-report.

Deadlock-free Transactions

For OPTIMISTIC SERIALIZABLE transactions, locks are not acquired sequentially. In this mode, keys can be accessed in any order because transaction locks are acquired in parallel with an additional check allowing Ignite to avoid deadlocks.

We need to introduce some concepts in order to describe how locks in SERIALIZABLE transactions work. In Ignite, each transaction is assigned a comparable version called XidVersion. Upon transaction commit, each entry that is written in the transaction is assigned a new comparable version called EntryVersion. An OPTIMISTIC SERIALIZABLE transaction with version XidVersionA fails with a TransactionOptimisticException if:

There is an ongoing PESSIMISTIC or non-serializable OPTIMISTIC transaction holding a lock on an entry of the SERIALIZABLE transaction.
There is another ongoing OPTIMISTIC SERIALIZABLE transaction with version XidVersionB such that XidVersionB > XidVersionA and this transaction holds a lock on an entry of the SERIALIZABLE transaction.
By the time the OPTIMISTIC SERIALIZABLE transaction acquires all required locks, there exists an entry with the current version different from the observed version before commit.

Handling Failed Transactions

A transaction might fail with the following exceptions:

Exception Description Solution

Exception	Description	Solution
`CacheException` caused by `TransactionTimeoutException`	`TransactionTimeoutException` is generated if the transaction times out.	To solve this exception, increase the timeout or make the transaction shorter.
`CacheException` caused by `TransactionTimeoutException`, which is caused by `TransactionDeadlockException`	This exception is thrown if the optimistic transaction fails for some reason. In most cases, this exception occurs when the data the transaction was trying to update was changed concurrently.	Rerun the transaction.
`TransactionOptimisticException`	This exception is thrown if the optimistic transaction fails for some reason. In most of the scenarios, this exception occurs when the data the transaction was trying to update was changed concurrently.	Rerun the transaction.
`TransactionRollbackException`	This exception occurs when a transaction is rolled back (automatically or manually). In this case, the data is consistent.	Since the data is in a consistent state, you can retry the transaction.
`TransactionHeuristicException`	An unlikely exception that happens due to an unexpected internal or communication issue. The exception exists to report problematic scenarios that were not foreseen by the transactional subsystem and were not handled by it properly.	The data might not stay consistent if the exception occurs. Reload the data and report to Ignite development community.

CacheException caused by TransactionTimeoutException

TransactionTimeoutException is generated if the transaction times out.

To solve this exception, increase the timeout or make the transaction shorter.

CacheException caused by TransactionTimeoutException, which is caused by TransactionDeadlockException

This exception is thrown if the optimistic transaction fails for some reason. In most cases, this exception occurs when the data the transaction was trying to update was changed concurrently.

Rerun the transaction.

TransactionOptimisticException

This exception is thrown if the optimistic transaction fails for some reason. In most of the scenarios, this exception occurs when the data the transaction was trying to update was changed concurrently.

Rerun the transaction.

TransactionRollbackException

This exception occurs when a transaction is rolled back (automatically or manually). In this case, the data is consistent.

Since the data is in a consistent state, you can retry the transaction.

TransactionHeuristicException

An unlikely exception that happens due to an unexpected internal or communication issue. The exception exists to report problematic scenarios that were not foreseen by the transactional subsystem and were not handled by it properly.

The data might not stay consistent if the exception occurs. Reload the data and report to Ignite development community.

JTA Transactions

GridGain supports Java Transactions API for XA resources. To perform the transactions, you set up a transaction manager and then pass the manager to transaction configuration:

public class Main {
    public static void main(String[] args) throws Exception {
        // Three steps to use JTA with Ignite
        // 1. Set up your TransactionManager of choice (here we use JOTM).
        // 2. Pass the TransactionManager to Ignite TransactionConfiguration.
        // 3. Obtain UserTransaction (usually from DI container) and use it to perform transactions.
        var jotm = new Jotm(true, false, new RmiLocalConfiguration());
        var txCfg = new TransactionConfiguration().setTxManagerFactory(jotm::getTransactionManager);
        var igniteCfg = new IgniteConfiguration().setTransactionConfiguration(txCfg);

        var ignite = Ignition.start(igniteCfg);
        igniteJtaDemo(ignite, jotm.getUserTransaction());
    }

    public static void igniteJtaDemo(Ignite ignite, UserTransaction userTx) throws Exception {
        var cacheCfg = new CacheConfiguration<Integer, Integer>("c")
                .setAtomicityMode(CacheAtomicityMode.TRANSACTIONAL);

        var cache = ignite.getOrCreateCache(cacheCfg);

        userTx.begin();
        cache.put(1, 1);
    }
}

The example above uses the following dependencies:

<dependency>
    <groupId>org.ow2.jotm</groupId>
    <artifactId>jotm-core</artifactId>
    <version>2.3.1-M1</version>
</dependency>

<dependency>
    <groupId>javax.resource</groupId>
    <artifactId>connector-api</artifactId>
    <version>1.5</version>
</dependency>

<dependency>
    <groupId>javax.transaction</groupId>
    <artifactId>jta</artifactId>
    <version>1.1</version>
</dependency>

Long Running Transactions Termination

Some cluster events trigger partition map exchange process and data rebalancing within an Ignite cluster to ensure even data distribution cluster-wide. An example of one such event is the cluster-topology-change event that takes place whenever a new node joins the cluster or an existing one leaves it. Plus, every time a new cache or SQL table is created, the partition map exchange gets triggered.

When the partition map exchange starts, Ignite acquires a global lock at a particular stage. The lock can’t be obtained while incomplete transactions are running in parallel. These transactions prevent the partition map exchange process from moving forward, thus blocking some operations such as a new node join process.

Use the TransactionConfiguration.setTxTimeoutOnPartitionMapExchange(…) method to set the maximum time allowed for your long-running transactions to block the partition map exchange. Once the timeout fires, all incomplete transactions are rolled back letting the partition map exchange proceed.

The example below shows how to configure the timeout:

<bean class="org.apache.ignite.configuration.IgniteConfiguration">

    <property name="transactionConfiguration">
        <bean class="org.apache.ignite.configuration.TransactionConfiguration">
            <!--Set the timeout to 20 seconds-->
            <property name="TxTimeoutOnPartitionMapExchange" value="20000"/>
        </bean>
    </property>

</bean>

// Create a configuration
IgniteConfiguration cfg = new IgniteConfiguration();

// Create a Transaction configuration
TransactionConfiguration txCfg = new TransactionConfiguration();

// Set the timeout to 20 seconds
txCfg.setTxTimeoutOnPartitionMapExchange(20000);

cfg.setTransactionConfiguration(txCfg);

// Start the node
Ignition.start(cfg);

var cfg = new IgniteConfiguration
{
    TransactionConfiguration = new TransactionConfiguration
    {
        DefaultTimeoutOnPartitionMapExchange = TimeSpan.FromSeconds(20)
    }
};
Ignition.Start(cfg);

This API is not presently available for C++. You can use XML configuration.

Also, consider using the TransactionConfiguration.setDefaultTxTimeout(…) method to modify the default transaction timeout in milliseconds. Initially, this value is defined by DFLT_TRANSACTION_TIMEOUT, which defaults to 0 - so there is no actual "default" timeout for transactions.

Examples:

<bean id="grid.cfg" class="org.apache.ignite.configuration.IgniteConfiguration">

        ...

        <property name="transactionConfiguration">
            <bean class="org.apache.ignite.configuration.TransactionConfiguration">
                <property name="defaultTxTimeout" value="30000"/>
            </bean>
        </property>

        ...

</bean>

IgniteConfiguration c = new IgniteConfiguration();
        TransactionConfiguration txCfg = c.getTransactionConfiguration();
        txCfg.setDefaultTxTimeout(30000)

var cfg = new IgniteConfiguration
{
    TransactionConfiguration = new TransactionConfiguration
    {
        DefaultTimeout = TimeSpan.FromSeconds(30)
    }
};

This API is not presently available for C++. You can use XML configuration.

Monitoring Transactions

Refer to the Monitoring Transactions section for the list of metrics that expose some transaction-related information.

You can also use the control script to get information about, or cancel, specific transactions being executed in the cluster.

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Last updated on Dec 04, 2024