Date: Tue, 19 Mar 2024 09:42:43 +0000 (UTC)
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Current state: ACCEPTED
Vote: http://mail-archives.apache.org/mod_mbox/samza-dev/201909.mbox/browser=
Discussion thread: http://mail-archives.apache.org/mod_mbox/samza-dev/201812.mbo=
x/%3CCABpE9c1_N4hFBsj7Yr5v_7q89SVwnm6Zr-MGuLz1e%3De8MchLkg%40mail.gmail.com=
%3E
JIRA: SAMZA-1983 - SEP-18 : St=
artpoints implementation in the core framework Resolved
=
em>
Authors: Daniel Nimishura, Shanthoosh Venkataraman<=
/em>
Released: Samza-1.4
To provide a common interface for =
external tools and services to rewind and fast-forward the starting offsets=
of any input stream of a samza application. This feature will provide the =
capabilities to manually manipulate the starting offsets by various positio=
n types and not only by specific offsets. Many of the current underlyi=
ng system consumers support different position types for seeking to an offs=
et on an input stream, such as seeks by timestamp, and are not generically =
exposed by the current framework.
A samza application consumes events from multiple input streams, applies=
transformations and produces the result to a output stream. A samza applic=
ation is typically comprised of multiple samza containers(physical processe=
s).
If a container of a samza application fails, upon restart it should resu=
me processing events where the failed container had left off. In order to e=
nable this, a samza container periodically checkpoints the current offset f=
or each partition of an input stream. In case of application failures,=
samza users would want their application to consume from a particular posi=
tion of a input stream(for instance, either due to a bug in their applicati=
on or due to a bug in upstream producer of the pipeline). The workflow=
currently supported in samza to update checkpoints:
- Users have to manually stop their running samza application.
- Create a configuration file in XML format and specify the starting offs=
et for each input topic partition.
- Run the samza-checkpoint tool which updates the checkpoint topic of the=
samza application with the new user-defined offsets.
- Users have to manually start their samza application again.
Using the samza-checkpoint tool is=
tedious and error prone, as it requires proper security access and potenti=
ally editing many offsets in a configuration file. In some cases, it can ca=
use a samza container to lose its checkpoints. In addition to the dangerous=
nature of modifying checkpoints directly, the checkpoint offsets are arbit=
rary strings with system-specific formats. This requires a different checkp=
oint tool for each system type (i.e. Kafka, Eventhub, Kinesis, etc...).
SSP - System stream partition. For example=
, on a Kafka stream called SomeEvent in the tracking cluster, the system is=
tracking, the stream is SomeEvent and the partition is a partition ID in t=
he stream.
JC - Job coordinator.
- Provide a simple and generic interface to manipulate starting offs=
ets per input stream partition instead of relying on system-specific c=
heckpoint tools and services. This allows flexibility to build REST API lay=
ers and tools on top of the common interface.
- Allow defining starting offsets on an input stream by SSP across a=
ll tasks or SSP per task.
- Framework level support for various offset types such as specific offse=
ts and timestamp-based offsets.
- Should support the different deployment models of samza viz standalone =
and yarn. Different API offerings of samza such as beam, SQL, high-level an=
d low-level API should be supported by the solution.
- Simplicity. Easy for developers and users to create tools and services =
to set starting offsets of a given Samza job.
- Rewinding or fast-fowarding state store changelogs in relation to the i=
nput streams. The challenge is that the changelog stream is typically log c=
ompacted.
- Providing a service that externally exposes a Startpoint API. Such serv=
ices require other core changes and will be explored in another SEP or desi=
gn document.
Different systems in Samza have different formats for checkpoint offsets=
and lack any contract that describes the offset format. To maintain backwa=
rds compatibility and to have better operability for setting starting offse=
ts, this solution introduces the concept of Startpoints and utilizes the ab=
stract metadata storage layer.
A Startpoint indicates what offset position a particular SSP should=
start consuming from. The Startpoint takes higher precedence&n=
bsp;than Checkpoints and defines the position type and th=
e position value of the position type. For example, if the Star=
tpoint position type is TIMESTAMP, then the position value is an epoch valu=
e in milliseconds. The Startpoint enforces a stricter contract for external=
tools and services to follow as opposed to the string offset value in the =
Checkpoint.
A requested Startpoint will be stored in the metadata store. This will b=
e decoupled from the checkpointed offsets in the checkpoint stream.
Startpoints are written to the metadata store under a readWrite namespac=
e using two key types: SSP-only and SSP+TaskName. For broadcast input strea=
ms, an SSP may span across multiple tasks and therefore, Startpoints are ap=
plied at the task level. For Startpoints on SSP-only keys, the task to SSP =
mappings are retrieved from the JobModel. Upon the subsequent start of the =
Samza job, the Startpoints are fanned out to a fanOut namespace in the meta=
data store. The below diagram illustrates the flow.
As with Checkpoints, Startpoints are applied to the starting offset of a=
n SSP in a task instance during the start up time of the SamzaContainer.
Once a particular Startpoint is applied to the starting offset of a SSP =
in a task instance, it is subsequently removed at the next offset commit.&n=
bsp;
Referenced in the General Workflow above.
The out-of-band metadata store used is described by the metadata store a=
bstraction feature (SAMZA-1786) from SEP-11. The Startpoints are stored within its own n=
amespaces in the metadata store.
Abstractly from the perspective of Startpoint operation, we think of the=
metadata store as a KV store and mapped as such:
{SSP=E2=86=92Startpoint} or {SSP+TaskName=E2=86=92Startpoin=
t}
TaskName is optional and is primarily for broadcast inputs where the sam=
e SSP spans across multiple tasks.
Upon the fan out, the Startpoints are mapped by task with the same struc=
ture as checkpoints:
{TaskName=E2=86=92{SSP=E2=86=92Startpoint}}
SamzaContainer is restarted before the first offset commit
- The Startpoint will be applied to the starting offset again upon restar=
t. However, this is identical to the same failure scenario for Checkpoints.=
JobCoordinator is restarted before all Startpoints are applied=
strong>
- Similar to the above failure scenario, except across multiple container=
s since restarting a JobCoordinator restarts all associated SamzaContainers=
.
/**
* Startpoint represents a position in a stream partition.
*/
public abstract class Startpoint {
private final long creationTimestamp;
/**
* Applies the {@link StartpointVisitor}'s visit methods to the {@link St=
artpoint}
* and returns the result of that operation.
* @param input the metadata associated with the startpoint.
* @param startpointVisitor the visitor of the startpoint.
* @return the result of applying the visitor on startpoint.
*/
public abstract <IN, OUT> OUT apply(IN input, StartpointVisitor<=
IN, OUT> startpointVisitor);
}
/**
* A {@link Startpoint} that represents the earliest offset in a stream par=
tition.
*/
public final class StartpointOldest extends Startpoint {
@Override
public <IN, OUT> OUT apply(IN input, StartpointVisitor<IN, OUT&g=
t; startpointVisitor) {
return startpointVisitor.visit(input, this);
}
}
/**
* A {@link Startpoint} that represents the latest offset in a stream parti=
tion.
*/
public final class StartpointUpcoming extends Startpoint {
@Override
public <IN, OUT> OUT apply(IN input, StartpointVisitor<IN, OUT&g=
t; startpointVisitor) {
return startpointVisitor.visit(input, this);
}
}
/**
* A {@link Startpoint} that represents a timestamp offset in a stream part=
ition.
*/
public final class StartpointTimestamp extends Startpoint {
private final Long timestampOffset;
}
/**
* A {@link Startpoint} that represents a specific offset in a stream parti=
tion.
*/
public final class StartpointSpecific extends Startpoint {
private final String specificOffset;
/**
* Getter for the specific offset.
* @return the specific offset.
*/
public String getSpecificOffset() {
return specificOffset;
}
@Override
public <IN, OUT> OUT apply(IN input, StartpointVisitor<IN, OUT&g=
t; startpointVisitor) {
return startpointVisitor.visit(input, this);
}
}
Referred to in Step 7 of the Loading Startpoints Upon Job Startup section =
;above.
public interf=
ace SystemAdmin {
...
/**
* Resolves the startpoint to a system specific offset.
* @param startpoint represents the startpoint.
* @param systemStreamPartition represents the system stream partition.
* @return the resolved offset.
*/
String resolveStartpointToOffset(SystemStreamPartition systemStreamPartit=
ion, Startpoint startpoint);
...
}
StartpointVisitor
/**
* A {@link SystemAdmin} implementation should implement this abstraction t=
o support {@link Startpoint} and the instance
* should visit via {@link Startpoint#apply(Object, StartpointVisitor)} wit=
hin the=20
* {@link SystemAdmin#resolveStartpointToOffset(SystemStreamPartition, Star=
tpoint)} implementation.
*/
public interface StartpointVisitor<IN, OUT> {
/**
* Performs a sequence of operations using the {@link IN} and {@link Star=
tpointSpecific} and returns the result of the execution.
* @param input the input metadata about the startpoint.
* @param startpointSpecific the {@link Startpoint} that represents the s=
pecific offset.
* @return the result of executing the operations defined by the visit me=
thod.
*/
default OUT visit(IN input, StartpointSpecific startpointSpecific) {
throw new UnsupportedOperationException("StartpointSpecific is not supp=
orted.");
}
/**
* Performs a sequence of operations using the {@link IN} and {@link Star=
tpointTimestamp} and returns the result of the execution.
* @param input the input metadata about the startpoint.
* @param startpointTimestamp the {@link Startpoint} that represents the =
timestamp.
* @return the result of executing the operations defined by the visit me=
thod.
*/
default OUT visit(IN input, StartpointTimestamp startpointTimestamp) {
throw new UnsupportedOperationException("StartpointTimestamp is not sup=
ported.");
}
/**
* Performs a sequence of operations using the {@link IN} and {@link Star=
tpointOldest} and returns the result of the execution.
* @param input the input metadata about the startpoint.
* @param startpointOldest the {@link Startpoint} that represents the ear=
liest offset.
* @return the result of executing the operations defined by the visit me=
thod.
*/
default OUT visit(IN input, StartpointOldest startpointOldest) {
throw new UnsupportedOperationException("StartpointOldest is not suppor=
ted.");
}
/**
* Performs a sequence of operations using the {@link IN} and {@link Star=
tpointUpcoming} and returns the result of the execution.
* @param input the input metadata about the startpoint.
* @param startpointUpcoming the {@link Startpoint} that represents the l=
atest offset.
* @return the result of executing the operations defined by the visit me=
thod.
*/
default OUT visit(IN input, StartpointUpcoming startpointUpcoming) {
throw new UnsupportedOperationException("StartpointUpcoming is not supp=
orted.");
}
}
StartpointManager is the main API =
to read and write Startpoints and is composed alongside the CheckpointManag=
er in the OffsetManager. It also provides the methods to fan out the Startp=
oints. The StartpointManager is system-implementation agnostic and handles the serialization an=
d deserialization of Startpoints into the metadata store.
/**
* The StartpointManager reads and writes {@link Startpoint} to the provide=
d {@link MetadataStore}
*
* The intention for the StartpointManager is to maintain a strong contract=
between the caller
* and how Startpoints are stored in the underlying MetadataStore.
*
* Startpoints are written in the MetadataStore using keys of two different=
formats:
* 1) {@link SystemStreamPartition} only
* 2) A combination of {@link SystemStreamPartition} and {@link TaskName}
*
* Startpoints are then fanned out to a fan out namespace in the MetadataSt=
ore by the
* {@link org.apache.samza.clustermanager.ClusterBasedJobCoordinator} or th=
e standalone
* {@link org.apache.samza.coordinator.JobCoordinator} upon startup and the
* {@link org.apache.samza.checkpoint.OffsetManager} gets the fan outs to s=
et the starting offsets per task and per
* {@link SystemStreamPartition}. The fan outs are deleted once the offsets=
are committed to the checkpoint.
*
* The read, write and delete methods are intended for external callers.
* The fan out methods are intended to be used within a job coordinator.
*/
public class StartpointManager {
/**
* Writes a {@link Startpoint} that defines the start position for a {@li=
nk SystemStreamPartition}.
* @param ssp The {@link SystemStreamPartition} to map the {@link Startpo=
int} against.
* @param startpoint Reference to a Startpoint object.
*/
public void writeStartpoint(SystemStreamPartition ssp, Startpoint startpo=
int) {...}
/**
* Writes a {@link Startpoint} that defines the start position for a {@li=
nk SystemStreamPartition} and {@link TaskName}.
* @param ssp The {@link SystemStreamPartition} to map the {@link Startpo=
int} against.
* @param taskName The {@link TaskName} to map the {@link Startpoint} aga=
inst.
* @param startpoint Reference to a Startpoint object.
*/
public void writeStartpoint(SystemStreamPartition ssp, TaskName taskName,=
Startpoint startpoint) {...}
/**
* Returns the last {@link Startpoint} that defines the start position fo=
r a {@link SystemStreamPartition}.
* @param ssp The {@link SystemStreamPartition} to fetch the {@link Start=
point} for.
* @return {@link Optional} of {@link Startpoint} for the {@link SystemSt=
reamPartition}.
* It is empty if it does not exist or if it is too stale.
*/
public Optional<Startpoint> readStartpoint(SystemStreamPartition ss=
p) {...}
/**
* Returns the {@link Startpoint} for a {@link SystemStreamPartition} and=
{@link TaskName}.
* @param ssp The {@link SystemStreamPartition} to fetch the {@link Start=
point} for.
* @param taskName The {@link TaskName} to fetch the {@link Startpoint} f=
or.
* @return {@link Optional} of {@link Startpoint} for the {@link SystemSt=
reamPartition} and {@link TaskName}.
* It is empty if it does not exist or if it is too stale.
*/
public Optional<Startpoint> readStartpoint(SystemStreamPartition ss=
p, TaskName taskName) {...}
/**
* Deletes the {@link Startpoint} for a {@link SystemStreamPartition}
* @param ssp The {@link SystemStreamPartition} to delete the {@link Star=
tpoint} for.
*/
public void deleteStartpoint(SystemStreamPartition ssp) {...}
/**
* Deletes the {@link Startpoint} for a {@link SystemStreamPartition} and=
{@link TaskName}.
* @param ssp ssp The {@link SystemStreamPartition} to delete the {@link =
Startpoint} for.
* @param taskName ssp The {@link TaskName} to delete the {@link Startpoi=
nt} for.
*/
public void deleteStartpoint(SystemStreamPartition ssp, TaskName taskName=
) {...}
/**
* The Startpoints that are written to with {@link #writeStartpoint(Syste=
mStreamPartition, Startpoint)} and with
* {@link #writeStartpoint(SystemStreamPartition, TaskName, Startpoint)} =
are moved from a "read-write" namespace
* to a "fan out" namespace.
* This method is not atomic or thread-safe. The intent is for the Samza =
Processor's coordinator to use this
* method to assign the Startpoints to the appropriate tasks.
* @param taskToSSPs Determines which {@link TaskName} each {@link System=
StreamPartition} maps to.
* @return The set of active {@link TaskName}s that were fanned out to.
*/
public Map<TaskName, Map<SystemStreamPartition, Startpoint>> =
fanOut(Map<TaskName, Set<SystemStreamPartition>> taskToSSPs) th=
rows IOException {...}
/**
* Read the fanned out {@link Startpoint}s for the given {@link TaskName}
* @param taskName to read the fan out Startpoints for
* @return fanned out Startpoints
*/
public Map<SystemStreamPartition, Startpoint> getFanOutForTask(Task=
Name taskName) throws IOException {...}
/**
* Deletes the fanned out {@link Startpoint#apply(Object, StartpointVisit=
or)} for the given {@link TaskName}
* @param taskName to delete the fan out Startpoints for
*/
public void removeFanOutForTask(TaskName taskName) {...}
}
All changes are backwards compatible. This is an add on feature and no c=
hanges to the existing checkpoint operations are required.
There may be opportunities where offset related APIs that are strongly c=
oupled to Checkpoints may be modified to handle both Startpoints and Checkp=
oints. Any such APIs will be deprecated until the next major version. =
No migration needed for this new feature.
Create a test job that logs the offset of the first event consumed per t=
ask and per SSP. Test using all Startpoint types.
Use the test job to test all combinations of:
- Job Coordinators (ex: ClusterbasedJobCoordinator, ZkJobCoordinator, etc=
..)
- Provided connectors (ex: Kafka, Eventhubs, etc..)
- Broadcast and non-broadcast streams
- Various input streams with various partition counts
A key part of the core Startpoint feature is for individual task instanc=
es to fetch the appropriate Startpoint keyed by SSP-only. The two approache=
s, have been explored=
with the analysis detailed in the following subsections. The fan-out strat=
egy is favored over the intent-ACK strategy. See analysis and explanation b=
elow.
See Pros
- Follows the natural progression of the JobCoordinator calculating the j=
ob model and then applying the info in the job model to fan out the SSP to =
SSP-Task Startpoints.
- Cleaner and simpler book keeping of Startpoints. SSP-only keyed Startpo=
ints are deleted after fan out and SSP+TaskName keyed Startpoints are delet=
ed upon offset commits.
- Will not work with the PassthroughJobCoordinator because it does not ha=
ve a leader election strategy. The fan-out approach requires a JC leader. W=
orkarounds will need to be explored during implementation for the small poo=
l of use cases where PassthroughJobCoordinator is needed.
This approach is rejected due to the weight of the cons and the complexi=
ty required to manage the intents and ACKs once they are applied to the sta=
rting offsets and no longer needed.
- Does not rely on Job Coordinator for consumption of Startpoints.
- Following the consumption of startpoints, metadata store will be pollut=
ed with SSP-only keyed startpoints and per-task-ACKs. Current implementatio=
n of the metadata store will bootstrap all the startpoints and ACKs until t=
hey are cleaned up.
- Task count may change during runtime due to the increase in the input s=
tream partition count. Therefore, new tasks will pick up the Startpoint unl=
ess all tasks prior to the increase in task count have written their ACKs a=
nd the cleanup process ran prior to the task-to-partition mapping. Startpoi=
nts should only apply to the state of the job upon startup and not to any c=
hanges during runtime.
Following is the workflow for the Intent/ACK approach:
1. The startpoint is written to the startpoint store.
2. The SamzaContainer's read the startpoint and acknowledge that they've ac=
ted on it.
3. After sufficient number of acks are received, an external agent purge th=
e startpoint. External agent can be either one of the running SamzaContaine=
r of the job or JobCoordinator of the job or a external daemon process.
In above workflow, an external agent will wait for the expected number o=
f ACKs to be published to startpoint-store, and then purge the startpoint. =
The expected number of ACK's is not a static number.
The container can acknowledge the startpoint at either one of the follow=
ing two levels of granularity:
1. Container-level: Currently, compared to YARN with static container co=
unt(defined by job.container.count), the number of containers in standalone=
is dynamic. Processors can join and leave the group at any point in time. =
For standalone, an external agent cannot determine if it had received suffi=
cient number of ACK's with certainty since number of containers is a moving=
number.
Standalone :
Let's consider the following scenario for standalone application. <=
/p>
A. Four processors are part of standalone application when =
the external agent watches for number of active processors in standalone ap=
plication.
B. External agent expects four ACK's to be written to the stor=
e before it can purge the startpoint.
C. Before any processor acks the startpoint, due to hardware f=
ailure, number of active processors gets reduced to three and a re-balance =
happens.
D. After re-balance, three live processors acks their correspo=
nding startpoint to the store and are running fine. External agent cannot c=
lear the start-point, since there're only three ACK's when compared to expe=
cted four.
Unless we change the coordination protocol in standalone to=
accommodate start-point, I'm not sure if we can ACK at this level to purge=
startpoints.
YARN :
There has been interesting recent developments, where we're planning to =
develop auto-scaling solution for YARN. In the immediate future, the number=
of containers in YARN will be not fixed and the above scenario described f=
or standalone will apply for YARN as well.
2. Task-level: The number of tasks can change dynamically at run-time ei=
ther due to increase in partition count of any of the input topics of the j=
ob or a new topic has matched the user-defined input topic-regex of the job=
. The above scenario described for standalone is still applicable here.
Previous explored solutions involved modifying the checkpoint offsets di=
rectly. Operationally, the Startpoint solution provides more safety because=
checkpoints are used for fault-tolerance. To prevent human error, the fram=
ework should not allow an external source to manipulate the checkpointed of=
fsets. The ability to set starting offsets out-of-band as Startpoints is de=
signed to do, provides the additional safety layer.
Another pain point for manipulating checkpoints is that it requires the =
Samza job to be stopped. Startpoints can be written while the job is runnin=
g.
See Analysis section for details on why the fan-out model is favored.
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