Cloud Datastore supports transactions. A transaction is an operation or set of operations that is atomic—either all of the operations in the transaction occur, or none of them occur. An application can perform multiple operations and calculations in a single transaction.

  1. Using transactions
  2. What can be done in a transaction
  3. Isolation and consistency
  4. Uses for transactions
  5. Transactional task enqueuing

Using transactions

A transaction is a set of Datastore operations on one or more entities. Each transaction is guaranteed to be atomic, which means that transactions are never partially applied. Either all of the operations in the transaction are applied, or none of them are applied. Transactions have a maximum duration of 60 seconds with a 10 second idle expiration time after 30 seconds.

An operation may fail when:

  • Too many concurrent modifications are attempted on the same entity group.
  • The transaction exceeds a resource limit.
  • The Datastore encounters an internal error.

In all these cases, the Datastore API returns an error.

Transactions are an optional feature of the Datastore; you're not required to use transactions to perform Datastore operations.

The datastore.RunInTransaction function runs the provided function in a transaction.

If the function returns nil, RunInTransaction attempts to commit the transaction, returning nil if it succeeds. If the function returns a non-nil error value, any Datastore changes are not applied and RunInTransaction returns that same error.

If RunInTransaction cannot commit the transaction because of a conflict it tries again, giving up after three attempts. This means that the transaction function should be idempotent (have the same result when executed multiple times). Note that datastore.Get is not idempotent when unmarshaling slice fields.

What can be done in a transaction

Cloud Datastore imposes restrictions on what can be done inside a single transaction.

All Datastore operations in a transaction must operate on entities in the same entity group if the transaction is a single-group transaction, or on entities in a maximum of twenty-five entity groups if the transaction is a cross-group transaction. This includes querying for entities by ancestor, retrieving entities by key, updating entities, and deleting entities. Notice that each root entity belongs to a separate entity group, so a single transaction cannot create or operate on more than one root entity unless it is a cross-group transaction.

When two or more transactions simultaneously attempt to modify entities in one or more common entity groups, only the first transaction to commit its changes can succeed; all the others will fail on commit. Because of this design, using entity groups limits the number of concurrent writes you can do on any entity in the groups. When a transaction starts, Cloud Datastore uses optimistic concurrency control by checking the last update time for the entity groups used in the transaction. Upon commiting a transaction for the entity groups, Cloud Datastore again checks the last update time for the entity groups used in the transaction. If it has changed since our initial check, an error is returned. For an explanation of entity groups, see the Datastore Overview page.

Isolation and consistency

Outside of transactions, the Datastore's isolation level is closest to read committed. Inside of transactions, serializable isolation is enforced. This means that another transaction cannot concurrently modify the data that is read or modified by this transaction. Read the serializable isolation wiki and the Transaction Isolation article for more information on isolation levels.

In a transaction, all reads reflect the current, consistent state of the Datastore at the time the transaction started. Queries and gets inside a transaction are guaranteed to see a single, consistent snapshot of the Datastore as of the beginning of the transaction. Entities and index rows in the transaction's entity group are fully updated so that queries return the complete, correct set of result entities, without the false positives or false negatives described in Transaction Isolation that can occur in queries outside of transactions.

This consistent snapshot view also extends to reads after writes inside transactions. Unlike with most databases, queries and gets inside a Datastore transaction do not see the results of previous writes inside that transaction. Specifically, if an entity is modified or deleted within a transaction, a query or get returns the original version of the entity as of the beginning of the transaction, or nothing if the entity did not exist then.

Uses for transactions

This example demonstrates one use of transactions: updating an entity with a new property value relative to its current value.

This requires a transaction because the value may be updated by another user after this code fetches the object, but before it saves the modified object. Without a transaction, the user's request uses the value of count prior to the other user's update, and the save overwrites the new value. With a transaction, the application is told about the other user's update. If the entity is updated during the transaction, then the transaction is retried until all steps are completed without interruption.

Another common use for transactions is to fetch an entity with a named key, or create it if it doesn't yet exist:

As before, a transaction is necessary to handle the case where another user is attempting to create or update an entity with the same string ID. Without a transaction, if the entity does not exist and two users attempt to create it, the second overwrites the first without knowing that it happened.

When a transaction fails, you can have your app retry the transaction until it succeeds, or you can let your users deal with the error by propagating it to your app's user interface level. You do not have to create a retry loop around every transaction.

Finally, you can use a transaction to read a consistent snapshot of the Datastore. This can be useful when multiple reads are needed to render a page or export data that must be consistent. These kinds of transactions are often called read-only transactions, since they perform no writes. Read-only single-group transactions never fail due to concurrent modifications, so you don't have to implement retries upon failure. However, cross-group transactions can fail due to concurrent modifications, so these should have retries. Committing and rolling back a read-only transaction are both no-ops.

Transactional task enqueuing

You can enqueue a task as part of a Datastore transaction, such that the task is only enqueued—and guaranteed to be enqueued—if the transaction is committed successfully. Once enqueued, the task is not guaranteed to execute immediately, so the task is not atomic with the transaction. Still, once enqueued, the task will retry until it succeeds. This applies to any task enqueued during a RunInTransaction function.

Transactional tasks are useful because they allow you to combine non-Datastore actions to a transaction that depend on the transaction succeeding (such as sending an email to confirm a purchase). You can also tie Datastore actions to the transaction, such as to commit changes to entity groups outside of the transaction if and only if the transaction succeeds.

An application cannot insert more than five transactional tasks into task queues duing a single transaction. Transactional tasks must not have user-specified names.

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