Fixed the parquet uint32 reading failure

Base/src/main/java/io/deephaven/base/FileUtils.java

@@ -16,19 +16,9 @@
 import java.util.regex.Pattern;
 
 public class FileUtils {
-    private final static FileFilter DIRECTORY_FILE_FILTER = new FileFilter() {
-        @Override
-        public boolean accept(File pathname) {
-            return pathname.isDirectory();
-        }
-    };
+    private final static FileFilter DIRECTORY_FILE_FILTER = File::isDirectory;
     private final static File[] EMPTY_DIRECTORY_ARRAY = new File[0];
-    private final static FilenameFilter DIRECTORY_FILENAME_FILTER = new FilenameFilter() {
-        @Override
-        public boolean accept(File dir, String name) {
-            return new File(dir, name).isDirectory();
-        }
-    };
+    private final static FilenameFilter DIRECTORY_FILENAME_FILTER = (dir, name) -> new File(dir, name).isDirectory();
     private final static String[] EMPTY_STRING_ARRAY = new String[0];
 
     public static final char URI_SEPARATOR_CHAR = '/';

extensions/parquet/table/src/main/java/io/deephaven/parquet/table/pagestore/topage/ToLongPageFromUnsignedInt.java

@@ -7,13 +7,15 @@
 import io.deephaven.chunk.attributes.Any;
 import org.jetbrains.annotations.NotNull;
 
+import static io.deephaven.util.QueryConstants.NULL_INT;
 import static io.deephaven.util.QueryConstants.NULL_INT_BOXED;
+import static io.deephaven.util.QueryConstants.NULL_LONG;
 
 public class ToLongPageFromUnsignedInt<ATTR extends Any> implements ToPage<ATTR, long[]> {
 
     private static final ToLongPageFromUnsignedInt INSTANCE = new ToLongPageFromUnsignedInt<>();
 
-    public static <ATTR extends Any> ToLongPageFromUnsignedInt<ATTR> create(Class<?> nativeType) {
+    public static <ATTR extends Any> ToLongPageFromUnsignedInt<ATTR> create(final Class<?> nativeType) {
         if (nativeType == null || long.class.equals(nativeType)) {
             // noinspection unchecked
             return INSTANCE;
@@ -42,11 +44,11 @@ public final Object nullValue() {
     }
 
     @Override
-    public final long[] convertResult(Object result) {
-        int[] from = (int[]) result;
-        long[] to = new long[from.length];
+    public final long[] convertResult(final Object result) {
+        final int[] from = (int[]) result;
+        final long[] to = new long[from.length];
         for (int i = 0; i < from.length; ++i) {
-            to[i] = Integer.toUnsignedLong(from[i]);
+            to[i] = from[i] == NULL_INT ? NULL_LONG : Integer.toUnsignedLong(from[i]);
         }
         return to;
     }

extensions/parquet/table/src/test/java/io/deephaven/parquet/table/ParquetTableReadWriteTest.java

@@ -57,6 +57,7 @@
 import io.deephaven.vector.*;
 import junit.framework.TestCase;
 import org.apache.commons.lang3.mutable.*;
+import org.apache.parquet.column.ColumnDescriptor;
 import org.apache.parquet.column.Encoding;
 import org.apache.parquet.column.statistics.Statistics;
 import org.apache.parquet.hadoop.metadata.ColumnChunkMetaData;
@@ -1581,6 +1582,50 @@ public void testReadOldParquetData() {
         readParquetFileFromGitLFS(new File(path)).select();
     }
 
+    /**
+     * The reference data is generated using:
+     *
+     * <pre>
+     * df = pandas.DataFrame.from_records(
+     *     data=[(-1, -1, -1), (2, 2, 2), (0, 0, 0), (5, 5, 5)],
+     *     columns=['uint8Col', 'uint16Col',  'uint32Col']
+     * )
+     * df['uint8Col'] = df['uint8Col'].astype(np.uint8)
+     * df['uint16Col'] = df['uint16Col'].astype(np.uint16)
+     * df['uint32Col'] = df['uint32Col'].astype(np.uint32)
+     *
+     * # Add some nulls
+     * df['uint8Col'][3] = df['uint16Col'][3] = df['uint32Col'][3] = None
+     * schema = pyarrow.schema([
+     *     pyarrow.field('uint8Col', pyarrow.uint8()),
+     *     pyarrow.field('uint16Col', pyarrow.uint16()),
+     *     pyarrow.field('uint32Col', pyarrow.uint32()),
+     * ])
+     * schema = schema.remove_metadata()
+     * table = pyarrow.Table.from_pandas(df, schema).replace_schema_metadata()
+     * writer = pyarrow.parquet.ParquetWriter('data_from_pyarrow.parquet', schema=schema)
+     * writer.write_table(table)
+     * </pre>
+     */
+    @Test
+    public void testReadUintParquetData() {
+        final String path = ParquetTableReadWriteTest.class.getResource("/ReferenceUintParquetData.parquet").getFile();
+        final Table fromDisk = readParquetFileFromGitLFS(new File(path)).select();
+
+        final ParquetMetadata metadata =
+                new ParquetTableLocationKey(new File(path).toURI(), 0, null, ParquetInstructions.EMPTY).getMetadata();
+        final List<ColumnDescriptor> columnsMetadata = metadata.getFileMetaData().getSchema().getColumns();
+        assertTrue(columnsMetadata.get(0).toString().contains("int32 uint8Col (INTEGER(8,false))"));
+        assertTrue(columnsMetadata.get(1).toString().contains("int32 uint16Col (INTEGER(16,false))"));
+        assertTrue(columnsMetadata.get(2).toString().contains("int32 uint32Col (INTEGER(32,false))"));
+
+        final Table expected = newTable(
+                charCol("uint8Col", (char) 255, (char) 2, (char) 0, NULL_CHAR),
+                charCol("uint16Col", (char) 65535, (char) 2, (char) 0, NULL_CHAR),
+                longCol("uint32Col", 4294967295L, 2L, 0L, NULL_LONG));
+        assertTableEquals(expected, fromDisk);
+    }
+
     @Test
     public void testVersionChecks() {
         assertFalse(ColumnChunkPageStore.hasCorrectVectorOffsetIndexes("0.0.0"));

py/server/tests/test_parquet.py

@@ -8,12 +8,13 @@
 import unittest
 import fnmatch
 
+import numpy as np
 import pandas
 import pyarrow.parquet
 
 from deephaven import DHError, empty_table, dtypes, new_table
 from deephaven import arrow as dharrow
-from deephaven.column import InputColumn, Column, ColumnType, string_col, int_col
+from deephaven.column import InputColumn, Column, ColumnType, string_col, int_col, char_col, long_col
 from deephaven.pandas import to_pandas, to_table
 from deephaven.parquet import (write, batch_write, read, delete, ColumnInstruction, ParquetFileLayout,
                                write_partitioned)
@@ -709,5 +710,28 @@ def test_write_with_definition(self):
         with self.assertRaises(Exception):
             write(table, "data_from_dh.parquet", table_definition=table_definition, col_definitions=col_definitions)
 
+    def test_unsigned_ints(self):
+        df = pandas.DataFrame.from_records(
+            data=[(-1, -1, -1), (2, 2, 2), (0, 0, 0)],
+            columns=['uint8Col', 'uint16Col',  'uint32Col']
+        )
+        df['uint8Col'] = df['uint8Col'].astype(np.uint8)
+        df['uint16Col'] = df['uint16Col'].astype(np.uint16)
+        df['uint32Col'] = df['uint32Col'].astype(np.uint32)
+
+        pyarrow.parquet.write_table(pyarrow.Table.from_pandas(df), 'data_from_pyarrow.parquet')
+        schema_from_disk = pyarrow.parquet.read_metadata("data_from_pyarrow.parquet").schema.to_arrow_schema()
+        self.assertTrue(schema_from_disk.field('uint8Col').type.equals(pyarrow.uint8()))
+        self.assertTrue(schema_from_disk.field('uint16Col').type.equals(pyarrow.uint16()))
+        self.assertTrue(schema_from_disk.field('uint32Col').type.equals(pyarrow.uint32()))
+
+        table_from_disk = read("data_from_pyarrow.parquet")
+        expected = new_table([
+            char_col("uint8Col", [255, 2, 0]),
+            char_col("uint16Col", [65535, 2, 0]),
+            long_col("uint32Col", [4294967295, 2, 0]),
+        ])
+        self.assert_table_equals(table_from_disk, expected)
+
 if __name__ == '__main__':
     unittest.main()