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.. distributed with this work for additional information
.. regarding copyright ownership.  The ASF licenses this file
.. to you under the Apache License, Version 2.0 (the
.. "License"); you may not use this file except in compliance
.. with the License.  You may obtain a copy of the License at

..   http://www.apache.org/licenses/LICENSE-2.0

.. Unless required by applicable law or agreed to in writing,
.. software distributed under the License is distributed on an
.. "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
.. KIND, either express or implied.  See the License for the
.. specific language governing permissions and limitations
.. under the License.

============
Tabular Data
============

While arrays (aka: :doc:`ValueVector <./vector>`) represent a one-dimensional sequence of
homogeneous values, data often comes in the form of two-dimensional sets of
heterogeneous data (such as database tables, CSV files...). Arrow provides
several abstractions to handle such data conveniently and efficiently.

Fields
======

Fields are used to denote the particular columns of tabular data.
A field, i.e. an instance of `Field`_, holds together a field name, a data
type, and some optional key-value metadata.

.. code-block:: Java

    // Create a column "document" of string type with metadata
    import org.apache.arrow.vector.types.pojo.ArrowType;
    import org.apache.arrow.vector.types.pojo.Field;
    import org.apache.arrow.vector.types.pojo.FieldType;

    Map<String, String> metadata = new HashMap<>();
    metadata.put("A", "Id card");
    metadata.put("B", "Passport");
    metadata.put("C", "Visa");
    Field document = new Field("document", new FieldType(true, new ArrowType.Utf8(), /*dictionary*/ null, metadata), /*children*/ null);

Schemas
=======

A `Schema`_ describes the overall structure consisting of any number of columns. It holds a sequence of fields together
with some optional schema-wide metadata (in addition to per-field metadata).

.. code-block:: Java

    // Create a schema describing datasets with two columns:
    // a int32 column "A" and a utf8-encoded string column "B"
    import org.apache.arrow.vector.types.pojo.ArrowType;
    import org.apache.arrow.vector.types.pojo.Field;
    import org.apache.arrow.vector.types.pojo.FieldType;
    import org.apache.arrow.vector.types.pojo.Schema;
    import static java.util.Arrays.asList;

    Map<String, String> metadata = new HashMap<>();
    metadata.put("K1", "V1");
    metadata.put("K2", "V2");
    Field a = new Field("A", FieldType.nullable(new ArrowType.Int(32, true)), null);
    Field b = new Field("B", FieldType.nullable(new ArrowType.Utf8()), null);
    Schema schema = new Schema(asList(a, b), metadata);

VectorSchemaRoot
================

A `VectorSchemaRoot`_ is a container for batches of data. Batches flow through
VectorSchemaRoot as part of a pipeline.

.. note::

    VectorSchemaRoot is somewhat analogous to tables or record batches in the
    other Arrow implementations in that they all are 2D datasets, but their
    usage is different.

The recommended usage is to create a single VectorSchemaRoot based on a known
schema and populate data over and over into that root in a stream of batches,
rather than creating a new instance each time (see `Flight`_ or
``ArrowFileWriter`` as examples). Thus at any one point, a VectorSchemaRoot may
have data or may have no data (say it was transferred downstream or not yet
populated).

Here is an example of creating a VectorSchemaRoot:

.. code-block:: Java

    BitVector bitVector = new BitVector("boolean", allocator);
    VarCharVector varCharVector = new VarCharVector("varchar", allocator);
    bitVector.allocateNew();
    varCharVector.allocateNew();
    for (int i = 0; i < 10; i++) {
      bitVector.setSafe(i, i % 2 == 0 ? 0 : 1);
      varCharVector.setSafe(i, ("test" + i).getBytes(StandardCharsets.UTF_8));
    }
    bitVector.setValueCount(10);
    varCharVector.setValueCount(10);

    List<Field> fields = Arrays.asList(bitVector.getField(), varCharVector.getField());
    List<FieldVector> vectors = Arrays.asList(bitVector, varCharVector);
    VectorSchemaRoot vectorSchemaRoot = new VectorSchemaRoot(fields, vectors);

Data can be loaded into/unloaded from a VectorSchemaRoot via `VectorLoader`_
and `VectorUnloader`_.  They handle converting between VectorSchemaRoot and
`ArrowRecordBatch`_ (a representation of a RecordBatch :ref:`IPC <format-ipc>`
message). For example:

.. code-block:: Java

    // create a VectorSchemaRoot root1 and convert its data into recordBatch
    VectorSchemaRoot root1 = new VectorSchemaRoot(fields, vectors);
    VectorUnloader unloader = new VectorUnloader(root1);
    ArrowRecordBatch recordBatch = unloader.getRecordBatch();

    // create a VectorSchemaRoot root2 and load the recordBatch
    VectorSchemaRoot root2 = VectorSchemaRoot.create(root1.getSchema(), allocator);
    VectorLoader loader = new VectorLoader(root2);
    loader.load(recordBatch);

A new VectorSchemaRoot can be sliced from an existing root without copying
data:

.. code-block:: Java

    // 0 indicates start index (inclusive) and 5 indicated length (exclusive).
    VectorSchemaRoot newRoot = vectorSchemaRoot.slice(0, 5);

.. _`ArrowRecordBatch`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/vector/ipc/message/ArrowRecordBatch.html
.. _`Field`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/vector/types/pojo/Field.html
.. _`Flight`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/flight/package-summary.html
.. _`Schema`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/vector/types/pojo/Schema.html
.. _`VectorLoader`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/vector/VectorLoader.html
.. _`VectorSchemaRoot`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/vector/VectorSchemaRoot.html
.. _`VectorUnloader`: https://arrow.apache.org/docs/java/reference/org/apache/arrow/vector/VectorUnloader.html
