sunchao commented on a change in pull request #32753:
URL: https://github.com/apache/spark/pull/32753#discussion_r654010520



##########
File path: 
sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedRleValuesReader.java
##########
@@ -340,6 +398,71 @@ public Binary readBinary(int len) {
     throw new UnsupportedOperationException("only readInts is valid.");
   }
 
+  @Override
+  public void skipIntegers(int total) {
+    int left = total;
+    while (left > 0) {
+      if (this.currentCount == 0) this.readNextGroup();
+      int n = Math.min(left, this.currentCount);
+      advance(n);
+      left -= n;
+    }
+  }
+
+  @Override
+  public void skipBooleans(int total) {
+    throw new UnsupportedOperationException("only skipIntegers is supported");

Review comment:
       I can change it to `only skipIntegers is valid`. It's because Parquet 
RLE encoding only support integers which is why all the others are 
unimplemented.

##########
File path: 
sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetIOSuite.scala
##########
@@ -378,11 +380,77 @@ class ParquetIOSuite extends QueryTest with ParquetTest 
with SharedSparkSession
       .withWriterVersion(PARQUET_1_0)
       .withCompressionCodec(GZIP)
       .withRowGroupSize(1024 * 1024)
-      .withPageSize(1024)
+      .withPageSize(pageSize)
+      .withDictionaryPageSize(dictionaryPageSize)
       .withConf(hadoopConf)
       .build()
   }
 
+  test("test multiple pages with different sizes and nulls") {

Review comment:
       Sure wil do

##########
File path: 
sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/VectorizedPlainValuesReader.java
##########
@@ -61,6 +61,14 @@ public final void readBooleans(int total, 
WritableColumnVector c, int rowId) {
     }
   }
 
+  @Override
+  public final void skipBooleans(int total) {
+    // TODO: properly vectorize this

Review comment:
       This follows a few other TODOs in the file when handling booleans. Yes I 
can file a JIRA too




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