$ mvn -q exec:java -Dexec.mainClass=example.SpecificMain In the sample above, for example, you could enable the fater coders as follows: To turn it on, set the system flag to true at runtime. In this first release, this feature is off by default. To ensure a smooth introduction of this change into production systems, this feature is controlled by a feature flag, the system property .use_custom_coders.
Java package org apache jar download code#
In release 1.9.0, we introduced a new approach to generating code that speeds up decoding of objects by more than 10% and encoding by more than 30% (future performance enhancements are underway). $ mvn compile # includes code generation via Avro Maven plugin $ mvn -q exec:java -Dexec.mainClass =example.SpecificMain From this directory, execute the following commands to build and run the example: This example code is included as a Maven project in the examples/java-example directory in the Avro docs. While this technique is the standard way to iterate through a data file, it’s also possible to use for (User user : dataFileReader) if performance is not a concern. This is a performance optimization that allows the DataFileReader to reuse the same User object rather than allocating a new User for every iteration, which can be very expensive in terms of object allocation and garbage collection if we deserialize a large data file. Note how we perform the iteration: we create a single User object which we store the current deserialized user in, and pass this record object to every call of dataFileReader.next.
Next we use the DataFileReader to iterate through the serialized Users and print the deserialized object to stdout. If there are differences between the two schemas, they are resolved according to the Schema Resolution specification.
Java package org apache jar download how to#
The writer’s schema is needed to know the order in which fields were written, while the reader’s schema is needed to know what fields are expected and how to fill in default values for fields added since the file was written. The data will be read using the writer’s schema included in the file and the schema provided by the reader, in this case the User class. We pass the DatumReader and the previously created File to a DataFileReader, analogous to the DataFileWriter, which reads both the schema used by the writer as well as the data from the file on disk. We create a SpecificDatumReader, analogous to the SpecificDatumWriter we used in serialization, which converts in-memory serialized items into instances of our generated class, in this case User.
avro-maven-plugin 1.11.1 generate-sources schema $ĭeserializing is very similar to serializing.
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