Database I/O Actions
Anything that you can execute on a database, whether it is a getting the result of a query
(myQuery.result
), creating a table (myTable.schema.create
), inserting data
(myTable += item
) or something else, is an instance of
DBIOAction, parameterized by the result type it will produce when you execute it.
Database I/O Actions can be combined with several different combinators (see the
DBIOAction class and DBIOAction object, which is also
available under the alias DBIO
, for details), but they will always be executed strictly sequentially and (at least
conceptually) in a single database session.
In most cases you will want to use the type aliases DBIO and StreamingDBIO for non-streaming and streaming Database I/O Actions. They omit the optional effect types supported by DBIOAction.
Executing Database I/O Actions
DBIOAction
s can be executed either with the goal of producing a fully materialized result or streaming
data back from the database.
Materialized
You can use run
to execute a DBIOAction
on a Database and produce a materialized result. This can
be, for example, a scalar query result (myTable.length.result
), a collection-valued query
result (myTable.to[Set].result
), or any other action. Every DBIOAction
supports this mode of
execution.
Execution of the action starts in the background when run
is called. The calling thread is not blocked. The
materialized result is returned as a Future which is completed asynchronously as soon as the result
is available:
Streaming
Collection-valued queries also support streaming results. In this case, the actual collection type
is ignored and elements are streamed directly from the result set through a Reactive Streams
Publisher
, which can be processed and consumed by Akka Streams.
Execution of the DBIOAction
does not start until a Subscriber
is attached to the stream. If multiple
Subscriber
s subscribe to the same Publisher
, each one triggers an independent execution of the
action.
Stream elements are signaled as soon as they become available in the streaming part of the DBIOAction
. The end of
the stream is signaled only after the entire action has completed. For example, when streaming inside a transaction
and all elements have been delivered successfully, the stream can still fail afterwards if the transaction cannot be
committed. The Subscriber
is notififed of this failure.
When streaming a JDBC result set, the next result page will be buffered in the background if the
Subscriber is not ready to receive more data, but all elements are signaled synchronously and the
result set is not advanced before synchronous processing is finished. This allows synchronous
callbacks to low-level JDBC values like Blob
which depend on the state of the result set. The
convenience method mapResult
is provided for this purpose:
Note: Some database systems may require session parameters to be set in a certain way to support streaming without caching all data at once in memory on the client side. For example, PostgreSQL requires both
.withStatementParameters(rsType = ResultSetType.ForwardOnly, rsConcurrency = ResultSetConcurrency.ReadOnly, fetchSize = n)
(with the desired page sizen
) and.transactionally
for proper streaming.
Composing Database I/O Actions
DBIOAction
s describe sequences of individual actions to execute in strictly sequential order on
one database session (at least conceptually), therefore the most commonly used combinators deal with
sequencing. Since a DBIOAction
eventually results in a Success
or Failure
, its combinators,
just like the ones on Future
, have to distinguish between successful and failed executions. Unless
specifically noted, all combinators only apply to successful actions. Any failure will abort the
sequence of execution and result in a failed Future
or Reactive Stream.
The available DBIO combinators are a purely functional subset of Future combinators. You should be familiar with working with Scala Futures before diving into DBIO combinators. Since the result of a database action is usually a Future, this knowledge is required anyway for composing database results and other asynchronous code.
Sequential Execution
The simplest combinator is DBIO.seq
which takes a varargs list of actions to run in sequence, discarding their return value. If you
need the return value, you can use andThen
to combine two actions and keep the result of the second one. If you need both return values of two
actions, there is the zip
combinator. For getting all result values from a sequence of actions (of compatible types), use
DBIO.sequence.
All these combinators work with pre-existing DBIOAction
s which are composed eagerly:
If an action depends on a previous action in the sequence, you have to compute it on the fly with
flatMap
or map.
These two methods plus filter
enable the use of for comprehensions for action sequencing. Since they take function
arguments, they also require an implicit ExecutionContext
on which to run the function. This
way Slick ensures that no non-database code is run on the database thread pool. This ExecutionContext should be
provided by your application or framework (e.g. Akka or Play).
Note: You should prefer the less flexible methods without an
ExecutionContext
where possible. The resulting actions can be executed more efficiently.
Similar to DBIO.sequence for upfront composition, there is DBIO.fold for working with sequences of actions and composing them based on the previous result.
Error Handling
You can use andFinally
to perform a cleanup action, no matter whether the previous action succeeded or failed. This is similar to using
try ... finally ...
in imperative Scala code. A more flexible version of
andFinally
is cleanUp.
It lets you transform the failure and decide how to fail the resulting action if both the original
one and the cleanup failed.
Note: For even more flexible error handling use asTry and failed. Unlike with andFinally and cleanUp the resulting actions cannot be used for streaming.
Primitives
You can convert a Future
into an action with DBIO.from.
This allows the result of the Future
to be used in an action sequence. A pre-existing value or
failure can be converted with DBIO.successful
and DBIO.failed, respectively.
Debugging
The named combinator names an
action. This name can be seen in debug logs if you enable the slick.basic.BasicBackend.action
logger.
Transactions and Pinned Sessions
When executing a DBIOAction
which is composed of several smaller actions, Slick acquires sessions from
the connection pool and releases them again as needed so that a session is not kept in use
unnecessarily while waiting for the result of a non-database computation (e.g. the function passed to
flatMap
that determines the next action to run). You can use withPinnedSession to
force the use of a single session, keeping the existing session open even when waiting for non-database computations.
All DBIOAction combinators which combine database actions without any non-database
computations in between (e.g.
andThen
or zip
applied to two database computations) can fuse these actions for more efficient execution, with the side-effect that
the fused action runs inside a single session, even without withPinnedSession
.
There is a related combinator called
transactionally
to force the use of a transaction. This guarantees that the entire DBIOAction
that is executed will
either succeed or fail atomically. Without it, all database actions run in auto-commit mode. The use of a transaction
always implies a pinned session.
Warning: Failure is not guaranteed to be atomic at the level of an individual
DBIOAction
that is wrapped withtransactionally
, so you need to be careful where you apply error recovery combinators. An actual database transaction is only created and committed or rolled back for the outermosttransactionally
action. Nestedtransactionally
actions simply execute inside the existing transaction without additional savepoints.
Rollbacks
In case you want to force a rollback, you can return DBIO.failed
within a DBIOAction
.
JDBC Interoperability
In order to drop down to the JDBC level for functionality that is not available in Slick, you can
use a SimpleDBIO
action which is run on a database thread and gets access to the JDBC Connection
:
If you need to access state of the database session across multiple SimpleDBIO
actions, make sure to
use withPinnedSession
or transactionally
accordingly (see above).