diff --git a/presto-hive/src/main/java/com/facebook/presto/hive/parquet/predicate/TupleDomainParquetPredicate.java b/presto-hive/src/main/java/com/facebook/presto/hive/parquet/predicate/TupleDomainParquetPredicate.java
index 46a13d645f132..f90cce3fc4970 100644
--- a/presto-hive/src/main/java/com/facebook/presto/hive/parquet/predicate/TupleDomainParquetPredicate.java
+++ b/presto-hive/src/main/java/com/facebook/presto/hive/parquet/predicate/TupleDomainParquetPredicate.java
@@ -79,7 +79,7 @@ public boolean matches(long numberOfRows, Map<ColumnDescriptor, Statistics<?>> s
             Statistics<?> columnStatistics = statistics.get(column);
 
             Domain domain;
-            Type type = getPrestoType(column);
+            Type type = getType(column);
             if (columnStatistics == null || columnStatistics.isEmpty()) {
                 // no stats for column
                 domain = Domain.all(type);
@@ -101,7 +101,7 @@ public boolean matches(Map<ColumnDescriptor, ParquetDictionaryDescriptor> dictio
 
         for (RichColumnDescriptor column : columns) {
             ParquetDictionaryDescriptor dictionaryDescriptor = dictionaries.get(column);
-            Domain domain = getDomain(getPrestoType(column), dictionaryDescriptor);
+            Domain domain = getDomain(getType(column), dictionaryDescriptor);
             if (domain != null) {
                 domains.put(column, domain);
             }
@@ -111,6 +111,21 @@ public boolean matches(Map<ColumnDescriptor, ParquetDictionaryDescriptor> dictio
         return effectivePredicate.overlaps(stripeDomain);
     }
 
+    private Type getType(RichColumnDescriptor column)
+    {
+        // we look at effective predicate domain because it more accurately matches the hive column
+        // than the type available in the parquet metadata passed here as RichColumnDescriptor
+        // for example varchar(len) hive column is translated to binary and then to varchar type using parquet metadata
+        Optional<Map<ColumnDescriptor, Domain>> predicateDomains = effectivePredicate.getDomains();
+        if (predicateDomains.isPresent()) {
+            Domain domain = predicateDomains.get().get(column);
+            if (domain != null) {
+                return domain.getType();
+            }
+        }
+        return getPrestoType(column);
+    }
+
     @VisibleForTesting
     public static Domain getDomain(Type type, long rowCount, Statistics<?> statistics)
     {
diff --git a/presto-hive/src/test/java/com/facebook/presto/hive/parquet/TestTupleDomainParquetPredicate.java b/presto-hive/src/test/java/com/facebook/presto/hive/parquet/TestTupleDomainParquetPredicate.java
index aa9234e3be86d..3224de696f5bf 100644
--- a/presto-hive/src/test/java/com/facebook/presto/hive/parquet/TestTupleDomainParquetPredicate.java
+++ b/presto-hive/src/test/java/com/facebook/presto/hive/parquet/TestTupleDomainParquetPredicate.java
@@ -13,15 +13,30 @@
  */
 package com.facebook.presto.hive.parquet;
 
+import com.facebook.presto.hive.parquet.predicate.ParquetDictionaryDescriptor;
+import com.facebook.presto.hive.parquet.predicate.TupleDomainParquetPredicate;
+import com.facebook.presto.spi.predicate.Domain;
+import com.facebook.presto.spi.predicate.TupleDomain;
 import com.facebook.presto.spi.predicate.ValueSet;
+import com.facebook.presto.spi.type.VarcharType;
 import org.testng.annotations.Test;
+import parquet.column.ColumnDescriptor;
 import parquet.column.statistics.BinaryStatistics;
 import parquet.column.statistics.BooleanStatistics;
 import parquet.column.statistics.DoubleStatistics;
 import parquet.column.statistics.FloatStatistics;
 import parquet.column.statistics.LongStatistics;
+import parquet.column.statistics.Statistics;
 import parquet.io.api.Binary;
+import parquet.schema.PrimitiveType;
+import parquet.schema.PrimitiveType.PrimitiveTypeName;
+import parquet.schema.Type.Repetition;
 
+import java.util.List;
+import java.util.Map;
+import java.util.Optional;
+
+import static com.facebook.presto.hive.parquet.ParquetEncoding.PLAIN_DICTIONARY;
 import static com.facebook.presto.hive.parquet.predicate.TupleDomainParquetPredicate.getDomain;
 import static com.facebook.presto.spi.predicate.Domain.all;
 import static com.facebook.presto.spi.predicate.Domain.create;
@@ -36,9 +51,14 @@
 import static com.facebook.presto.spi.type.SmallintType.SMALLINT;
 import static com.facebook.presto.spi.type.TinyintType.TINYINT;
 import static com.facebook.presto.spi.type.VarcharType.createUnboundedVarcharType;
+import static com.facebook.presto.spi.type.VarcharType.createVarcharType;
 import static io.airlift.slice.Slices.utf8Slice;
 import static java.lang.Float.floatToRawIntBits;
+import static java.util.Collections.singletonList;
+import static java.util.Collections.singletonMap;
 import static org.testng.Assert.assertEquals;
+import static org.testng.Assert.assertTrue;
+import static parquet.column.statistics.Statistics.getStatsBasedOnType;
 
 public class TestTupleDomainParquetPredicate
 {
@@ -166,6 +186,46 @@ public void testFloat()
         assertEquals(getDomain(REAL, 10, floatColumnStats(maximum, minimum)), create(ValueSet.all(REAL), false));
     }
 
+    @Test
+    public void testMatchesWithStatistics()
+    {
+        RichColumnDescriptor column = getColumn();
+        String value = "Test";
+        TupleDomain<ColumnDescriptor> effectivePredicate = getEffectivePredicate(column, createVarcharType(255), value);
+        List<RichColumnDescriptor> columns = singletonList(column);
+        TupleDomainParquetPredicate predicate = new TupleDomainParquetPredicate(effectivePredicate, columns);
+        Statistics stats = getStatsBasedOnType(column.getType());
+        stats.setNumNulls(1L);
+        stats.setMinMaxFromBytes(value.getBytes(), value.getBytes());
+        assertTrue(predicate.matches(2, singletonMap(column, stats)));
+    }
+
+    @Test
+    public void testMatchesWithDescriptors()
+    {
+        RichColumnDescriptor column = getColumn();
+        String value = "Test2";
+        TupleDomain<ColumnDescriptor> effectivePredicate = getEffectivePredicate(column, createVarcharType(255), value);
+        List<RichColumnDescriptor> columns = singletonList(column);
+        TupleDomainParquetPredicate predicate = new TupleDomainParquetPredicate(effectivePredicate, columns);
+        ParquetDictionaryPage page = new ParquetDictionaryPage(utf8Slice(value), 2, PLAIN_DICTIONARY);
+        assertTrue(predicate.matches(singletonMap(column, new ParquetDictionaryDescriptor(column, Optional.of(page)))));
+    }
+
+    private TupleDomain<ColumnDescriptor> getEffectivePredicate(RichColumnDescriptor column, VarcharType type, String value)
+    {
+        ColumnDescriptor predicateColumn = new ColumnDescriptor(column.getPath(), column.getType(), 0, 0);
+        Domain predicateDomain = Domain.singleValue(type, utf8Slice(value));
+        Map<ColumnDescriptor, Domain> predicateColumns = singletonMap(predicateColumn, predicateDomain);
+        return TupleDomain.withColumnDomains(predicateColumns);
+    }
+
+    private RichColumnDescriptor getColumn()
+    {
+        PrimitiveType type = new PrimitiveType(Repetition.OPTIONAL, PrimitiveTypeName.BINARY, "Test column");
+        return new RichColumnDescriptor(new String[] {"path"}, type, 0, 0);
+    }
+
     private static FloatStatistics floatColumnStats(float minimum, float maximum)
     {
         FloatStatistics statistics = new FloatStatistics();