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https://issues.apache.org/jira/browse/ARROW-1780?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16416392#comment-16416392
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ASF GitHub Bot commented on ARROW-1780:
---------------------------------------
laurentgo commented on a change in pull request #1759: ARROW-1780 - [WIP] JDBC
Adapter to convert Relational Data objects to Arrow Data Format Vector Objects
URL: https://github.com/apache/arrow/pull/1759#discussion_r177589405
##########
File path:
java/adapter/jdbc/src/main/java/org/apache/arrow/adapter/jdbc/JdbcToArrowUtils.java
##########
@@ -0,0 +1,343 @@
+/**
+ * Licensed to the Apache Software Foundation (ASF) under one
+ * or more contributor license agreements. See the NOTICE file
+ * 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.
+ */
+
+package org.apache.arrow.adapter.jdbc;
+
+import org.apache.arrow.vector.*;
+import org.apache.arrow.vector.types.DateUnit;
+import org.apache.arrow.vector.types.TimeUnit;
+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 java.nio.charset.Charset;
+import java.sql.*;
+import java.util.ArrayList;
+import java.util.List;
+
+import static org.apache.arrow.vector.types.FloatingPointPrecision.DOUBLE;
+import static org.apache.arrow.vector.types.FloatingPointPrecision.SINGLE;
+
+
+/**
+ * Class that does most of the work to convert JDBC ResultSet data into Arrow
columnar format Vector objects.
+ *
+ * @since 0.10.0
+ */
+public class JdbcToArrowUtils {
+
+ private static final int DEFAULT_BUFFER_SIZE = 256;
+
+ /**
+ * Create Arrow {@link Schema} object for the given JDBC {@link
ResultSetMetaData}.
+ *
+ * This method currently performs following type mapping for JDBC SQL data
types to corresponding Arrow data types.
+ *
+ * CHAR --> ArrowType.Utf8
+ * NCHAR --> ArrowType.Utf8
+ * VARCHAR --> ArrowType.Utf8
+ * NVARCHAR --> ArrowType.Utf8
+ * LONGVARCHAR --> ArrowType.Utf8
+ * LONGNVARCHAR --> ArrowType.Utf8
+ * NUMERIC --> ArrowType.Decimal(precision, scale)
+ * DECIMAL --> ArrowType.Decimal(precision, scale)
+ * BIT --> ArrowType.Bool
+ * TINYINT --> ArrowType.Int(8, signed)
+ * SMALLINT --> ArrowType.Int(16, signed)
+ * INTEGER --> ArrowType.Int(32, signed)
+ * BIGINT --> ArrowType.Int(64, signed)
+ * REAL --> ArrowType.FloatingPoint(FloatingPointPrecision.SINGLE)
+ * FLOAT --> ArrowType.FloatingPoint(FloatingPointPrecision.SINGLE)
+ * DOUBLE --> ArrowType.FloatingPoint(FloatingPointPrecision.DOUBLE)
+ * BINARY --> ArrowType.Binary
+ * VARBINARY --> ArrowType.Binary
+ * LONGVARBINARY --> ArrowType.Binary
+ * DATE --> ArrowType.Date(DateUnit.MILLISECOND)
+ * TIME --> ArrowType.Time(TimeUnit.MILLISECOND, 32)
+ * TIMESTAMP --> ArrowType.Timestamp(TimeUnit.MILLISECOND, timezone=null)
+ * CLOB --> ArrowType.Utf8
+ * BLOB --> ArrowType.Binary
+ *
+ * @param rsmd
+ * @return {@link Schema}
+ * @throws SQLException
+ */
+ public static Schema jdbcToArrowSchema(ResultSetMetaData rsmd) throws
SQLException {
+
+ assert rsmd != null;
+
+// ImmutableList.Builder<Field> fields = ImmutableList.builder();
+ List<Field> fields = new ArrayList<>();
+ int columnCount = rsmd.getColumnCount();
+ for (int i = 1; i <= columnCount; i++) {
+ String columnName = rsmd.getColumnName(i);
+ switch (rsmd.getColumnType(i)) {
+ case Types.BOOLEAN:
+ case Types.BIT:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Bool()), null));
+ break;
+ case Types.TINYINT:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Int(8, true)), null));
+ break;
+ case Types.SMALLINT:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Int(16, true)), null));
+ break;
+ case Types.INTEGER:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Int(32, true)), null));
+ break;
+ case Types.BIGINT:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Int(64, true)), null));
+ break;
+ case Types.NUMERIC:
+ case Types.DECIMAL:
+ int precision = rsmd.getPrecision(i);
+ int scale = rsmd.getScale(i);
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Decimal(precision, scale)), null));
+ break;
+ case Types.REAL:
+ case Types.FLOAT:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.FloatingPoint(SINGLE)), null));
+ break;
+ case Types.DOUBLE:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.FloatingPoint(DOUBLE)), null));
+ break;
+ case Types.CHAR:
+ case Types.NCHAR:
+ case Types.VARCHAR:
+ case Types.NVARCHAR:
+ case Types.LONGVARCHAR:
+ case Types.LONGNVARCHAR:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Utf8()), null));
+ break;
+ case Types.DATE:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Date(DateUnit.MILLISECOND)), null));
+ break;
+ case Types.TIME:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Time(TimeUnit.MILLISECOND, 32)), null));
+ break;
+ case Types.TIMESTAMP:
+ // timezone is null
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Timestamp(TimeUnit.MILLISECOND, null)), null));
+ break;
+ case Types.BINARY:
+ case Types.VARBINARY:
+ case Types.LONGVARBINARY:
+ fields.add(new Field(columnName, FieldType.nullable(new
ArrowType.Binary()), null));
+ break;
+ case Types.ARRAY:
+ // not handled
+// fields.add(new Field("list", FieldType.nullable(new
ArrowType.List()), null));
Review comment:
field is ignored, so doesn't that mess up with the resulting schema? (number
of fields different between JDBC and Arrow)?
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> JDBC Adapter for Apache Arrow
> -----------------------------
>
> Key: ARROW-1780
> URL: https://issues.apache.org/jira/browse/ARROW-1780
> Project: Apache Arrow
> Issue Type: New Feature
> Reporter: Atul Dambalkar
> Assignee: Atul Dambalkar
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.10.0
>
>
> At a high level the JDBC Adapter will allow upstream apps to query RDBMS data
> over JDBC and get the JDBC objects converted to Arrow objects/structures. The
> upstream utility can then work with Arrow objects/structures with usual
> performance benefits. The utility will be very much similar to C++
> implementation of "Convert a vector of row-wise data into an Arrow table" as
> described here -
> https://arrow.apache.org/docs/cpp/md_tutorials_row_wise_conversion.html
> The utility will read data from RDBMS and covert the data into Arrow
> objects/structures. So from that perspective this will Read data from RDBMS,
> If the utility can push Arrow objects to RDBMS is something need to be
> discussed and will be out of scope for this utility for now.
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