apache/flink · error · IOException

Failed to deserialize an element from the source. If you are

Error message

Failed to deserialize an element from the source. If you are using user-defined serialization (Value and Writable types), check the serialization functions.
Serializer is {serializer}

What it means

Thrown by tryDeserialize in IndexLookupGeneratorFunction when deserialization fails with an exception other than EOFException. The message advises checking user-defined serialization (Value and Writable types) and includes the serializer's toString() for diagnostics. The original exception is chained as the cause.

Source

Thrown at flink-connectors/flink-connector-datagen/src/main/java/org/apache/flink/connector/datagen/functions/IndexLookupGeneratorFunction.java:154

            }
        } catch (Exception e) {
            throw new IOException("Serializing the source elements failed: " + e.getMessage(), e);
        }
        this.elementsSerialized = baos.toByteArray();
    }

    private OUT tryDeserialize() throws IOException {
        try {
            return serializer.deserialize(input);
        } catch (EOFException eof) {
            throw new NoSuchElementException(
                    "Reached the end of the collection. This could be caused by issues with the "
                            + "serializer or by calling the map() function more times than there "
                            + "are elements in the collection. Make sure that you set the number "
                            + "of records to be produced by the DataGeneratorSource equal to the "
                            + "number of elements in the collection.");
        } catch (Exception e) {
            throw new IOException(
                    "Failed to deserialize an element from the source. "
                            + "If you are using user-defined serialization (Value and Writable "
                            + "types), check the serialization functions.\nSerializer is "
                            + serializer,
                    e);
        }
    }

    private void buildLookup() throws IOException {
        for (long i = 0; i < numElements; i++) {
            lookupMap.put(i, tryDeserialize());
        }
    }

    private void trySerialize(Iterable<OUT> elements) {
        try {
            serializeElements(elements);
        } catch (IOException e) {

View on GitHub (pinned to 2f3c205e92)

Solutions

Inspect the chained cause exception for the specific deserialization failure reason.
Verify the custom type's readFields/write symmetry — every field written must be read in the same order and format.
Check if the TypeSerializer version is compatible across Flink upgrades.
Test serialize+deserialize round-trip in a unit test for the custom type.

Defensive patterns

Strategy: try-catch

Validate before calling

// Verify custom Value/Writable type round-trips correctly
MyValue original = new MyValue(...);
ByteArrayOutputStream baos = new ByteArrayOutputStream();
DataOutputViewStreamWrapper out = new DataOutputViewStreamWrapper(baos);
typeInfo.createSerializer(config).serialize(original, out);
DataInputViewStreamWrapper in = new DataInputViewStreamWrapper(
    new ByteArrayInputStream(baos.toByteArray()));
MyValue restored = typeInfo.createSerializer(config).deserialize(in);
assert original.equals(restored); // verify symmetry

Try / catch

try {
    fn.open(readerContext);
} catch (IOException e) {
    if (e.getMessage().startsWith("Failed to deserialize an element")) {
        // inspect e.getCause() for the specific deserialization error
        // check custom Value/Writable readFields() vs write() symmetry
    }
    throw e;
}

Prevention

For custom Value/Writable types, ensure readFields mirrors write exactly.
Write a unit test that serializes then deserializes every element and asserts equality.
Keep serializer version stable across Flink upgrades, or implement TypeSerializerSnapshot migration.

When it happens

Trigger: During buildLookup or map deserialization, serializer.deserialize(input) throws a non-EOF exception. This indicates corrupt serialized data, a serializer version mismatch, or a bug in a custom Value/Writable readFields() method.

Common situations: A custom type's readFields() does not mirror write() correctly; serializer snapshot version mismatch after upgrading Flink; state corruption in the serialized byte array.

Related errors

AI-assisted analysis of apache/flink@2f3c205e92 (2026-08-14). Data as JSON: /api/errors/4ab4ad950237bb96. Report an issue: GitHub.