These release notes discuss important aspects, such as configuration, behavior, or dependencies, that changed between Flink 1.9 and Flink 1.10. Please read these notes carefully if you are planning to upgrade your Flink version to 1.10.
s3-hadoop and s3-presto filesystems do no longer use class relocations and need to be loaded through plugins but now seamlessly integrate with all credential providers. Other filesystems are strongly recommended to be only used as plugins as we will continue to remove relocations.
The Flink client now also respects the configured classloading policy, i.e.,
child-first classloading. Previously, only cluster
components such as the job manager or task manager supported this setting.
This does mean that users might get different behaviour in their programs, in
which case they should configure the classloading policy explicitly to use
parent-first classloading, which was the previous (hard-coded) behaviour.
was rolled out with Flink 1.5.0, we changed how slots are allocated from
TaskManagers (TMs). Instead of evenly allocating the slots from all registered
TMs, we had the tendency to exhaust a TM before using another one. To use a
scheduling strategy that is more similar to the pre-FLIP-6 behaviour, where
Flink tries to spread out the workload across all currently available TMs, one
cluster.evenly-spread-out-slots: true in the
All highly available artifacts stored by Flink will now be stored under
HA_STORAGE_DIR configured by
HA_CLUSTER_ID configured by
When using the
--yarnship command line option, resource directories and jar
files will be added to the classpath in lexicographical order with resources
directories appearing first.
The Flink CLI no longer supports the deprecated command line options
-yn/--yarncontainer, which were used to specify the number of containers to
start on YARN. This option has been deprecated since the introduction of
All Flink users are advised to remove this command line option.
The Flink CLI no longer supports the deprecated command line options
-yst/--yarnstreaming, which were used to disable eager pre-allocation of memory.
All Flink users are advised to remove this command line option.
Flink’s Mesos integration now rejects all expired offers instead of only 4. This improves the situation where Fenzo holds on to a lot of expired offers without giving them back to the Mesos resource manager.
Flink’s scheduler was refactored with the goal of making scheduling strategies
customizable in the future. Using the legacy scheduler is discouraged as it will
be removed in a future release. However, users that experience issues related to
scheduling can fallback to the legacy scheduler by setting
legacy in their
flink-conf.yaml for the time
being. Note, however, that using the legacy scheduler with the Pipelined Region
enabled has the following caveats:
uptimemetric will not be reset after restarting a job due to task failure (FLINK-15918).
Note that in the default
flink-conf.yaml, the Pipelined Region Failover
Strategy is already enabled. That is, users that want to use the legacy
scheduler and cannot accept aforementioned caveats should make sure that
jobmanager.execution.failover-strategy is set to
full or not set at all.
Beginning from this release, Flink can be compiled and run with Java 11. All Java 8 artifacts can be also used with Java 11. This means that users that want to run Flink with Java 11 do not have to compile Flink themselves.
When starting Flink with Java 11, the following warnings may be logged:
WARNING: An illegal reflective access operation has occurred WARNING: Illegal reflective access by org.apache.flink.core.memory.MemoryUtils (file:/opt/flink/flink-1.10.0/lib/flink-dist_2.11-1.10.0.jar) to constructor java.nio.DirectByteBuffer(long,int) WARNING: Please consider reporting this to the maintainers of org.apache.flink.core.memory.MemoryUtils WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations WARNING: All illegal access operations will be denied in a future release WARNING: An illegal reflective access operation has occurred WARNING: Illegal reflective access by org.apache.flink.api.java.ClosureCleaner (file:/home/flinkuser/.m2/repository/org/apache/flink/flink-core/1.10.0/flink-core-1.10.0.jar) to field java.lang.String.value WARNING: Please consider reporting this to the maintainers of org.apache.flink.api.java.ClosureCleaner WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations WARNING: All illegal access operations will be denied in a future release WARNING: An illegal reflective access operation has occurred WARNING: Illegal reflective access by org.jboss.netty.util.internal.ByteBufferUtil (file:/home/flinkuser/.m2/repository/io/netty/netty/3.10.6.Final/netty-3.10.6.Final.jar) to method java.nio.DirectByteBuffer.cleaner() WARNING: Please consider reporting this to the maintainers of org.jboss.netty.util.internal.ByteBufferUtil WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations WARNING: All illegal access operations will be denied in a future release WARNING: An illegal reflective access operation has occurred WARNING: Illegal reflective access by com.esotericsoftware.kryo.util.UnsafeUtil (file:/home/flinkuser/.m2/repository/com/esotericsoftware/kryo/kryo/2.24.0/kryo-2.24.0.jar) to constructor java.nio.DirectByteBuffer(long,int,java.lang.Object) WARNING: Please consider reporting this to the maintainers of com.esotericsoftware.kryo.util.UnsafeUtil WARNING: Use --illegal-access=warn to enable warnings of further illegal reflective access operations WARNING: All illegal access operations will be denied in a future release
These warnings are considered harmless and will be addressed in future Flink releases.
Lastly, note that the connectors for Cassandra, Hive, HBase, and Kafka 0.8–0.11 have not been tested with Java 11 because the respective projects did not provide Java 11 support at the time of the Flink 1.10.0 release.
With FLIP-49, a new memory model has been introduced for the task executor. New configuration options have been introduced to control the memory consumption of the task executor process. This affects all types of deployments: standalone, YARN, Mesos, and the new active Kubernetes integration. The memory model of the job manager process has not been changed yet but it is planned to be updated as well.
If you try to reuse your previous Flink configuration without any adjustments, the new memory model can result in differently computed memory parameters for the JVM and, thus, performance changes.
Please, check the user documentation for more details.
The following options have been removed and have no effect anymore:
|Deprecated/removed config option||Note|
Check also the description of the new option
|taskmanager.memory.off-heap||Support for on-heap managed memory has been removed, leaving off-heap managed memory as the only possibility|
|taskmanager.memory.preallocate||Pre-allocation is no longer supported, and managed memory is always allocated lazily|
The following options, if used, are interpreted as other new options in order to maintain backwards compatibility where it makes sense:
|Deprecated config option||Interpreted as|
The container cut-off configuration options,
containerized.heap-cutoff-min, have no effect for task executor processes
anymore but they still have the same semantics for the JobManager process.
Together with the introduction of the new Task Executor Memory
Model, the memory consumption of the RocksDB state backend will be
limited by the total amount of Flink Managed Memory, which can be configured via
Furthermore, users can tune RocksDB’s write/read memory ratio
state.backend.rocksdb.memory.write-buffer-ratio, by default
0.5) and the
reserved memory fraction for indices/filters
state.backend.rocksdb.memory.high-prio-pool-ratio, by default
details and advanced configuration options can be found in the Flink user
table.exec.resource.sort.memory have been deprecated. Beginning from Flink
1.10, these config options are interpreted as weight hints instead of absolute
memory requirements. Flink choses sensible default weight hints which should
not be adjustment by users.
raw is a reserved keyword now and must be escaped with
backticks when used as a SQL field or function name.
Some indexed properties for table connectors have been flattened and renamed
for a better user experience when writing DDL statements. This affects the
Kafka Connector properties
connector.specific-offsets. Furthermore, the Elasticsearch Connector
connector.hosts is affected. The aforementioned, old properties are
deprecated and will be removed in future versions. Please consult the Table
for the new property names.
registerDataSet() have been
deprecated in favor of
createTemporaryView(), which better adheres to the
corresponding SQL term.
scan() method has been deprecated in favor of the
registerTableSink() become deprecated in favor
approach expects only a set of string properties as a description of a
TableSource or TableSink instead of an instance of a class in case of the
deprecated methods. This in return makes it possible to reliably store those
definitions in catalogs.
insertInto(String path, String... pathContinued) has been removed in
favor of in
All the newly introduced methods accept a String identifier which will be parsed into a 3-part identifier. The parser supports quoting the identifier. It also requires escaping any reserved SQL keywords.
ExternalCatalog API has been dropped. This includes:
ExternalCatalog(and all dependent classes, e.g.,
Users are advised to use the new Catalog API.
IllegalArgumentException now if the configured value cannot be parsed into
the required type. In previous Flink releases the default value was returned
in such cases.
The default restart delay for all shipped restart strategies, i.e.,
failure-rate, has been raised to 1 s (from originally 0 s).
Previously, if the user had set
restart-strategy.fixed-delay.delay but had not configured the option
restart-strategy, the cluster-level restart strategy would have been
fixed-delay. Now the cluster-level restart strategy is only determined by
the config option
restart-strategy and whether checkpointing is enabled. See
“Task Failure Recovery”
The config option
been renamed to
taskmanager.network.blocking-shuffle.type. Moreover, the
default value of the aforementioned config option has been changed from
file. The reason is that TaskManagers running on YARN with
easily exceed the memory budget of their container, due to incorrectly accounted
memory-mapped files memory usage.
The non-credit-based network flow control code was removed alongside of the
taskmanager.network.credit-model. Flink will now always
use credit-based flow control.
The configuration option
high-availability.job.delay has been removed
since it is no longer used.
Background cleanup of expired state with TTL
is activated by default now for all state backends shipped with Flink.
Note that the RocksDB state backend implements background cleanup by employing
a compaction filter. This has the caveat that even if a Flink job does not
store state with TTL, a minor performance penalty during compaction is incurred.
Users that experience noticeable performance degradation during RocksDB
compaction can disable the TTL compaction filter by setting the config option
StateTtlConfig#Builder#cleanupInBackground() has been deprecated because the
background cleanup of state with TTL is already enabled by default.
The default timer store has been changed from Heap to RocksDB for the RocksDB
state backend to support asynchronous snapshots for timer state and better
scalability, with less than 5% performance cost. Users that find the performance
decline critical can set
flink-conf.yaml to restore the old behavior.
StateTtlConfig#TimeCharacteristic has been removed in favor of
We have added a new method
MapState#isEmpty() which enables users to check
whether a map state is empty. The new method is 40% faster than
mapState.keys().iterator().hasNext() when using the RocksDB state backend.
We have again released our own RocksDB build (FRocksDB) which is based on RocksDB version 5.17.2 with several feature backports for the Write Buffer Manager to enable limiting RocksDB’s memory usage. The decision to release our own RocksDB build was made because later RocksDB versions suffer from a performance regression under certain workloads.
Logging in RocksDB (e.g., logging related to flush, compaction, memtable
creation, etc.) has been disabled by default to prevent disk space from being
filled up unexpectedly. Users that need to enable logging should implement their
RocksDBOptionsFactory that creates
DBOptions instances with
InfoLogLevel set to
In previous Flink releases users may encounter an
restoring from a RocksDB savepoint containing large KV pairs. For that reason
we introduced a configurable memory limit in the
with a default value of 2 MB. RocksDB’s WriteBatch will flush before the
consumed memory limit is reached. If needed, the limit can be tuned via the
state.backend.rocksdb.write-batch-size config option in
Beginning from this release, PyFlink does not support Python 2. This is because Python 2 has reached end of life on January 1, 2020, and several third-party projects that PyFlink depends on are also dropping Python 2 support.
InfluxdbReporter now silently skips values that are unsupported by
InfluxDB, such as
flink-connector-kinesis is now licensed under the Apache License, Version 2.0, and its artifacts will be deployed to Maven central as part of the Flink releases. Users no longer need to build the Kinesis connector from source themselves.
ExecutionConfig#getGlobalJobParameters has been changed to never return
ExecutionConfig#setGlobalJobParameters(GlobalJobParameters) will not accept
null values anymore.
Executor) must be non-blocking now. Any blocking operation should be executed
asynchronously, e.g., using the given executor.
HighAvailabilityServices have been split up into client-side
ClientHighAvailabilityServices and cluster-side
When implementing custom high availability services, users should follow this
separation by overriding the factory method
HighAvailabilityServices#getWebMonitorLeaderRetriever() should no
longer be implemented since it has been deprecated.
HighAvailabilityServices should implement
LeaderElectionService#confirmLeadership(UUID, String) now takes an
additional second argument, which is the address under which the leader will be
reachable. All custom
LeaderElectionService implementations will need to be
deprecated now. Users should use
MailboxExecutor to run actions that require
synchronization with the task’s thread (e.g. collecting output produced by an
external thread). The methods
MailboxExecutor#tryYield() can be used for actions that need to give up
control to other actions temporarily, e.g., if the current operator is
MailboxExecutor can be accessed by using
AsyncWaitOperator for an example usage).
ConfigurableOptionsFactory have been
deprecated in favor of
JobGraphs which set the
ResourceSpec created by Flink versions <
1.10 are no longer compatible with Flink >=
If you want to migrate these jobs to Flink >=
1.10 you will have to stop the job with a savepoint and then resume it from this savepoint on the Flink >=
DataStream creates a
ContinuousFileReaderOperator that used to be chained to subsequent operators.
However, chained operator do not trigger processing time timers correctly, leading to bugs in watermark assigners (FLINK-19109). As a workaround,
ContinuousFileReaderOperator is disabled. Flink 1.11.2 and later fixes the underlying problem and re-allows chaining.