115 lines
4.7 KiB
Markdown
115 lines
4.7 KiB
Markdown
Use in Java {#flatbuffers_guide_use_java}
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==============
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## Before you get started
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Before diving into the FlatBuffers usage in Java, it should be noted that
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the [Tutorial](@ref flatbuffers_guide_tutorial) page has a complete guide to
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general FlatBuffers usage in all of the supported languages (including Java).
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This page is designed to cover the nuances of FlatBuffers usage,
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specific to Java.
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You should also have read the [Building](@ref flatbuffers_guide_building)
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documentation to build `flatc` and should be familiar with
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[Using the schema compiler](@ref flatbuffers_guide_using_schema_compiler) and
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[Writing a schema](@ref flatbuffers_guide_writing_schema).
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## FlatBuffers Java code location
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The code for the FlatBuffers Java library can be found at
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`flatbuffers/java/com/google/flatbuffers`. You can browse the library on the
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[FlatBuffers GitHub page](https://github.com/google/flatbuffers/tree/master/
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java/com/google/flatbuffers).
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## Testing the FlatBuffers Java libraries
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The code to test the libraries can be found at `flatbuffers/tests`.
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The test code for Java is located in [JavaTest.java](https://github.com/google
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/flatbuffers/blob/master/tests/JavaTest.java).
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To run the tests, use either [JavaTest.sh](https://github.com/google/
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flatbuffers/blob/master/tests/JavaTest.sh) or [JavaTest.bat](https://github.com/
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google/flatbuffers/blob/master/tests/JavaTest.bat), depending on your operating
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system.
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*Note: These scripts require that [Java](https://www.oracle.com/java/index.html)
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is installed.*
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## Using the FlatBuffers Java library
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*Note: See [Tutorial](@ref flatbuffers_guide_tutorial) for a more in-depth
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example of how to use FlatBuffers in Java.*
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FlatBuffers supports reading and writing binary FlatBuffers in Java.
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To use FlatBuffers in your own code, first generate Java classes from your
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schema with the `--java` option to `flatc`.
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Then you can include both FlatBuffers and the generated code to read
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or write a FlatBuffer.
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For example, here is how you would read a FlatBuffer binary file in Java:
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First, import the library and generated code. Then, you read a FlatBuffer binary
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file into a `byte[]`. You then turn the `byte[]` into a `ByteBuffer`, which you
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pass to the `getRootAsMyRootType` function:
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.java}
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import MyGame.Example.*;
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import com.google.flatbuffers.FlatBufferBuilder;
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// This snippet ignores exceptions for brevity.
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File file = new File("monsterdata_test.mon");
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RandomAccessFile f = new RandomAccessFile(file, "r");
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byte[] data = new byte[(int)f.length()];
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f.readFully(data);
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f.close();
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ByteBuffer bb = ByteBuffer.wrap(data);
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Monster monster = Monster.getRootAsMonster(bb);
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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Now you can access the data from the `Monster monster`:
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~{.java}
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short hp = monster.hp();
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Vec3 pos = monster.pos();
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~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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## Storing dictionaries in a FlatBuffer
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FlatBuffers doesn't support dictionaries natively, but there is support to
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emulate their behavior with vectors and binary search, which means you
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can have fast lookups directly from a FlatBuffer without having to unpack
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your data into a `Dictionary` or similar.
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To use it:
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- Designate one of the fields in a table as the "key" field. You do this
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by setting the `key` attribute on this field, e.g.
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`name:string (key)`.
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You may only have one key field, and it must be of string or scalar type.
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- Write out tables of this type as usual, collect their offsets in an
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array.
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- Instead of calling standard generated method,
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e.g.: `Monster.createTestarrayoftablesVector`,
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call `createSortedVectorOfTables` (from the `FlatBufferBuilder` object).
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which will first sort all offsets such that the tables they refer to
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are sorted by the key field, then serialize it.
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- Now when you're accessing the FlatBuffer, you can use
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the `ByKey` accessor to access elements of the vector, e.g.:
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`monster.testarrayoftablesByKey("Frodo")`.
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which returns an object of the corresponding table type,
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or `null` if not found.
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`ByKey` performs a binary search, so should have a similar
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speed to `Dictionary`, though may be faster because of better caching.
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`ByKey` only works if the vector has been sorted, it will
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likely not find elements if it hasn't been sorted.
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## Text parsing
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There currently is no support for parsing text (Schema's and JSON) directly
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from Java, though you could use the C++ parser through native call
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interfaces available to each language. Please see the
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C++ documentation for more on text parsing.
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<br>
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