In a nutshell, this feature exposes Flink’s managed keyed (partitioned) state (see Working with State) to the outside world and allows the user to query a job’s state from outside Flink. For some scenarios, queryable state eliminates the need for distributed operations/transactions with external systems such as key-value stores which are often the bottleneck in practice. In addition, this feature may be particularly useful for debugging purposes.
MemoryStateBackend
or FsStateBackend
, does not work
with copies when retrieving values but instead directly references the stored values, read-modify-write
patterns are unsafe and may cause the queryable state server to fail due to concurrent modifications.
The RocksDBStateBackend
is safe from these issues.
Before showing how to use the Queryable State, it is useful to briefly describe the entities that compose it. The Queryable State feature consists of three main entities:
QueryableStateClient
, which (potentially) runs outside the Flink cluster and submits the user queries,QueryableStateClientProxy
, which runs on each TaskManager
(i.e. inside the Flink cluster) and is responsible
for receiving the client’s queries, fetching the requested state from the responsible Task Manager on his behalf, and
returning it to the client, andQueryableStateServer
which runs on each TaskManager
and is responsible for serving the locally stored state.The client connects to one of the proxies and sends a request for the state associated with a specific
key, k
. As stated in Working with State, keyed state is organized in
Key Groups, and each TaskManager
is assigned a number of these key groups. To discover which TaskManager
is
responsible for the key group holding k
, the proxy will ask the JobManager
. Based on the answer, the proxy will
then query the QueryableStateServer
running on that TaskManager
for the state associated with k
, and forward the
response back to the client.
To enable queryable state on your Flink cluster, you just have to copy the
flink-queryable-state-runtime_2.11-1.7.2.jar
from the opt/
folder of your Flink distribution,
to the lib/
folder. Otherwise, the queryable state feature is not enabled.
To verify that your cluster is running with queryable state enabled, check the logs of any
task manager for the line: "Started the Queryable State Proxy Server @ ..."
.
Now that you have activated queryable state on your cluster, it is time to see how to use it. In order for a state to be visible to the outside world, it needs to be explicitly made queryable by using:
QueryableStateStream
, a convenience object which acts as a sink and offers its incoming values as queryable
state, orstateDescriptor.setQueryable(String queryableStateName)
method, which makes the keyed state represented by the
state descriptor, queryable.The following sections explain the use of these two approaches.
Calling .asQueryableState(stateName, stateDescriptor)
on a KeyedStream
returns a QueryableStateStream
which offers
its values as queryable state. Depending on the type of state, there are the following variants of the asQueryableState()
method:
ListState
sink as it would result in an ever-growing
list which may not be cleaned up and thus will eventually consume too much memory.
The returned QueryableStateStream
can be seen as a sink and cannot be further transformed. Internally, a
QueryableStateStream
gets translated to an operator which uses all incoming records to update the queryable state
instance. The updating logic is implied by the type of the StateDescriptor
provided in the asQueryableState
call.
In a program like the following, all records of the keyed stream will be used to update the state instance via the
ValueState.update(value)
:
This acts like the Scala API’s flatMapWithState
.
Managed keyed state of an operator
(see Using Managed Keyed State)
can be made queryable by making the appropriate state descriptor queryable via
StateDescriptor.setQueryable(String queryableStateName)
, as in the example below:
queryableStateName
parameter may be chosen arbitrarily and is only
used for queries. It does not have to be identical to the state's own name.
This variant has no limitations as to which type of state can be made queryable. This means that this can be used for
any ValueState
, ReduceState
, ListState
, MapState
, AggregatingState
, and the currently deprecated FoldingState
.
So far, you have set up your cluster to run with queryable state and you have declared (some of) your state as queryable. Now it is time to see how to query this state.
For this you can use the QueryableStateClient
helper class. This is available in the flink-queryable-state-client
jar which must be explicitly included as a dependency in the pom.xml
of your project along with flink-core
, as shown below:
For more on this, you can check how to set up a Flink program.
The QueryableStateClient
will submit your query to the internal proxy, which will then process your query and return
the final result. The only requirement to initialize the client is to provide a valid TaskManager
hostname (remember
that there is a queryable state proxy running on each task manager) and the port where the proxy listens. More on how
to configure the proxy and state server port(s) in the Configuration Section.
With the client ready, to query a state of type V
, associated with a key of type K
, you can use the method:
The above returns a CompletableFuture
eventually holding the state value for the queryable state instance identified
by queryableStateName
of the job with ID jobID
. The key
is the key whose state you are interested in and the
keyTypeInfo
will tell Flink how to serialize/deserialize it. Finally, the stateDescriptor
contains the necessary
information about the requested state, namely its type (Value
, Reduce
, etc) and the necessary information on how
to serialize/deserialize it.
The careful reader will notice that the returned future contains a value of type S
, i.e. a State
object containing
the actual value. This can be any of the state types supported by Flink: ValueState
, ReduceState
, ListState
, MapState
,
AggregatingState
, and the currently deprecated FoldingState
.
valueState.get()
, or iterate over
the contained <K, V>
entries, e.g. using the mapState.entries()
, but you cannot
modify them. As an example, calling the add()
method on a returned list state will throw an
UnsupportedOperationException
.
QueryableStateClient.shutdown()
when unused in order to free
resources.
The following example extends the CountWindowAverage
example
(see Using Managed Keyed State)
by making it queryable and shows how to query this value:
Once used in a job, you can retrieve the job ID and then query any key’s current state from this operator:
The following configuration parameters influence the behaviour of the queryable state server and client.
They are defined in QueryableStateOptions
.
query.server.ports
: the server port range of the queryable state server. This is useful to avoid port clashes if more
than 1 task managers run on the same machine. The specified range can be: a port: “9123”, a range of ports: “50100-50200”,
or a list of ranges and or points: “50100-50200,50300-50400,51234”. The default port is 9067.query.server.network-threads
: number of network (event loop) threads receiving incoming requests for the state server (0 => #slots)query.server.query-threads
: number of threads handling/serving incoming requests for the state server (0 => #slots).query.proxy.ports
: the server port range of the queryable state proxy. This is useful to avoid port clashes if more
than 1 task managers run on the same machine. The specified range can be: a port: “9123”, a range of ports: “50100-50200”,
or a list of ranges and or points: “50100-50200,50300-50400,51234”. The default port is 9069.query.proxy.network-threads
: number of network (event loop) threads receiving incoming requests for the client proxy (0 => #slots)query.proxy.query-threads
: number of threads handling/serving incoming requests for the client proxy (0 => #slots).