David Mollitor created SPARK-59621:
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Summary: Serialize StatusUpdate manually (Externalizable) to avoid
Enumeration/BigDecimal overhead
Key: SPARK-59621
URL: https://issues.apache.org/jira/browse/SPARK-59621
Project: Spark
Issue Type: Improvement
Components: Spark Core
Affects Versions: 4.1.0
Reporter: David Mollitor
h3. Description
{{CoarseGrainedClusterMessages.StatusUpdate}} is sent from executor to driver
on *every task state change* ({{{}RUNNING{}}} at start,
{{{}FINISHED{}}}/{{{}FAILED{}}}/{{{}KILLED{}}} at end) – roughly two or more
per task, on the driver's RPC intake path.
Measuring its Java-serialized size (a fresh {{ObjectOutputStream}} per RPC, so
no class-descriptor caching) shows an empty-payload {{StatusUpdate}} is {*}1713
bytes{*}, and two fields account for ~75% of it:
||Field||Serialized bytes||
|{{state}} (a Scala {{Enumeration}} value)|642|
|{{taskCpus}} (a {{{}BigDecimal{}}})|638|
|{{resources}} (empty {{{}Map{}}})|150|
|{{data}} (empty {{{}SerializableBuffer{}}})|68|
|full {{StatusUpdate}}|1713|
A Scala {{Enumeration.Value}} serializes a reference to its enclosing
{{Enumeration}} object, so it drags in the whole {{TaskState}} object;
{{scala.math.BigDecimal}} drags in
{{java.math.BigDecimal}} + {{BigInteger}} + {{MathContext}} + {{RoundingMode}}
descriptors. The actual payload is ~31 bytes.
Make {{StatusUpdate}} {{Externalizable}} with a compact manual encoding,
mirroring
{{UpdateBlockInfo}} in the same message family and reusing
{{{}TaskDescription{}}}'s exact wire form for the fractional-CPU {{BigDecimal}}
({{{}CpuAmount.toDisplayString{}}} / {{{}CpuAmount.normalize{}}}): {{state}} as
one byte ({{{}.id{}}}), {{taskCpus}} as its normalized decimal string, {{data}}
via {{{}SerializableBuffer{}}}'s existing channel-based serialization (no extra
copy for large results), and {{resources}} as a size-prefixed nested map.
This shrinks the empty-payload message from *1713 bytes to 191 bytes* (~9x
smaller), cutting steady serialization/GC/bandwidth on a per-task-frequency
control message. It is behavior-preserving (all fields round-trip; fractional
CPUs exactly).
Wire-compat: this is an internal driver<->executor RPC within a single
application, and Java serialization is already documented as not stable across
Spark versions.
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