[Kernel][Defaults] Support reading parquet files with legacy 3-level …

…repeated types (#3083)

## Description
When legacy mode is enabled in Spark, array physical types are stored
slightly different from the standard format.

Standard mode (default):
```
optional group readerFeatures (LIST) {
  repeated group list {
    optional binary element (STRING);
  }
}
```

When write legacy mode is enabled (`spark.sql.parquet.writeLegacyFormat
= true`):
```
optional group readerFeatures (LIST) {
  repeated group bag {
    optional binary array (STRING);
  }
}
```

TODO: We need to handle the 2-level lists. Will post a separate PR. The
challenge is with generating or finding the Parquet files with 2-level
lists.

## How was this patch tested?
Added tests

Fixes #3082

connectors/golden-tables/src/main/resources/golden/parquet-all-types-legacy-format/_delta_log/00000000000000000000.json

@@ -0,0 +1,4 @@
+{"commitInfo":{"timestamp":1715358358979,"operation":"WRITE","operationParameters":{"mode":"Append","partitionBy":"[]"},"isolationLevel":"Serializable","isBlindAppend":true,"operationMetrics":{"numFiles":"1","numOutputRows":"200","numOutputBytes":"20934"},"engineInfo":"Apache-Spark/3.5.0 Delta-Lake/3.2.0-SNAPSHOT","txnId":"01d57c6f-6073-484f-b832-5cf368644e4b"}}
+{"metaData":{"id":"fb723383-fb90-4346-a846-ccdac9a3204b","format":{"provider":"parquet","options":{}},"schemaString":"{\"type\":\"struct\",\"fields\":[{\"name\":\"ByteType\",\"type\":\"byte\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ShortType\",\"type\":\"short\",\"nullable\":true,\"metadata\":{}},{\"name\":\"IntegerType\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}},{\"name\":\"LongType\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}},{\"name\":\"FloatType\",\"type\":\"float\",\"nullable\":true,\"metadata\":{}},{\"name\":\"DoubleType\",\"type\":\"double\",\"nullable\":true,\"metadata\":{}},{\"name\":\"decimal\",\"type\":\"decimal(10,2)\",\"nullable\":true,\"metadata\":{}},{\"name\":\"BooleanType\",\"type\":\"boolean\",\"nullable\":true,\"metadata\":{}},{\"name\":\"StringType\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"BinaryType\",\"type\":\"binary\",\"nullable\":true,\"metadata\":{}},{\"name\":\"DateType\",\"type\":\"date\",\"nullable\":true,\"metadata\":{}},{\"name\":\"TimestampType\",\"type\":\"timestamp\",\"nullable\":true,\"metadata\":{}},{\"name\":\"TimestampNTZType\",\"type\":\"timestamp_ntz\",\"nullable\":true,\"metadata\":{}},{\"name\":\"nested_struct\",\"type\":{\"type\":\"struct\",\"fields\":[{\"name\":\"aa\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ac\",\"type\":{\"type\":\"struct\",\"fields\":[{\"name\":\"aca\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}}]},\"nullable\":true,\"metadata\":{}}]},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_prims\",\"type\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_arrays\",\"type\":{\"type\":\"array\",\"elementType\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_structs\",\"type\":{\"type\":\"array\",\"elementType\":{\"type\":\"struct\",\"fields\":[{\"name\":\"ab\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}}]},\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_prims\",\"type\":{\"type\":\"map\",\"keyType\":\"integer\",\"valueType\":\"long\",\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_rows\",\"type\":{\"type\":\"map\",\"keyType\":\"integer\",\"valueType\":{\"type\":\"struct\",\"fields\":[{\"name\":\"ab\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}}]},\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_arrays\",\"type\":{\"type\":\"map\",\"keyType\":\"long\",\"valueType\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}}]}","partitionColumns":[],"configuration":{},"createdTime":1715358356845}}
+{"protocol":{"minReaderVersion":3,"minWriterVersion":7,"readerFeatures":["timestampNtz"],"writerFeatures":["timestampNtz"]}}
+{"add":{"path":"part-00000-5afb67f1-094a-4a15-922e-c1eb96683964-c000.snappy.parquet","partitionValues":{},"size":20934,"modificationTime":1715358358904,"dataChange":true,"stats":"{\"numRecords\":200,\"minValues\":{\"ByteType\":-128,\"ShortType\":1,\"IntegerType\":1,\"LongType\":2,\"FloatType\":0.234,\"DoubleType\":234234.23,\"decimal\":123.52,\"StringType\":\"1\",\"DateType\":\"1970-01-01\",\"TimestampType\":\"1970-01-01T06:30:23.523Z\",\"TimestampNTZType\":\"1970-01-03T17:03:54.000\",\"nested_struct\":{\"aa\":\"1\",\"ac\":{\"aca\":1}}},\"maxValues\":{\"ByteType\":127,\"ShortType\":199,\"IntegerType\":199,\"LongType\":200,\"FloatType\":46.566,\"DoubleType\":4.661261177E7,\"decimal\":24580.48,\"StringType\":\"99\",\"DateType\":\"1970-02-16\",\"TimestampType\":\"1970-02-23T22:48:01.077Z\",\"TimestampNTZType\":\"1971-06-24T11:56:06.000\",\"nested_struct\":{\"aa\":\"99\",\"ac\":{\"aca\":199}}},\"nullCount\":{\"ByteType\":3,\"ShortType\":4,\"IntegerType\":9,\"LongType\":8,\"FloatType\":8,\"DoubleType\":4,\"decimal\":3,\"BooleanType\":3,\"StringType\":4,\"BinaryType\":4,\"DateType\":4,\"TimestampType\":4,\"TimestampNTZType\":3,\"nested_struct\":{\"aa\":14,\"ac\":{\"aca\":22}},\"array_of_prims\":200,\"array_of_arrays\":200,\"array_of_structs\":200,\"map_of_prims\":200,\"map_of_rows\":200,\"map_of_arrays\":200}}"}}

connectors/golden-tables/src/main/resources/golden/parquet-all-types/_delta_log/00000000000000000000.json

@@ -1,4 +1,4 @@
-{"commitInfo":{"timestamp":1713368423544,"operation":"WRITE","operationParameters":{"mode":"Append","partitionBy":"[]"},"isolationLevel":"Serializable","isBlindAppend":true,"operationMetrics":{"numFiles":"1","numOutputRows":"200","numOutputBytes":"30312"},"engineInfo":"Apache-Spark/3.5.0 Delta-Lake/3.2.0-SNAPSHOT","txnId":"d711414e-08c1-46d0-a5c5-d5faad64d59e"}}
-{"metaData":{"id":"7027c1fa-69c4-4867-ace8-6f8c44a022d0","format":{"provider":"parquet","options":{}},"schemaString":"{\"type\":\"struct\",\"fields\":[{\"name\":\"ByteType\",\"type\":\"byte\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ShortType\",\"type\":\"short\",\"nullable\":true,\"metadata\":{}},{\"name\":\"IntegerType\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}},{\"name\":\"LongType\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}},{\"name\":\"FloatType\",\"type\":\"float\",\"nullable\":true,\"metadata\":{}},{\"name\":\"DoubleType\",\"type\":\"double\",\"nullable\":true,\"metadata\":{}},{\"name\":\"decimal\",\"type\":\"decimal(10,2)\",\"nullable\":true,\"metadata\":{}},{\"name\":\"BooleanType\",\"type\":\"boolean\",\"nullable\":true,\"metadata\":{}},{\"name\":\"StringType\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"BinaryType\",\"type\":\"binary\",\"nullable\":true,\"metadata\":{}},{\"name\":\"DateType\",\"type\":\"date\",\"nullable\":true,\"metadata\":{}},{\"name\":\"TimestampType\",\"type\":\"timestamp\",\"nullable\":true,\"metadata\":{}},{\"name\":\"TimestampNTZType\",\"type\":\"timestamp_ntz\",\"nullable\":true,\"metadata\":{}},{\"name\":\"nested_struct\",\"type\":{\"type\":\"struct\",\"fields\":[{\"name\":\"aa\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ac\",\"type\":{\"type\":\"struct\",\"fields\":[{\"name\":\"aca\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}}]},\"nullable\":true,\"metadata\":{}}]},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_prims\",\"type\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_arrays\",\"type\":{\"type\":\"array\",\"elementType\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_structs\",\"type\":{\"type\":\"array\",\"elementType\":{\"type\":\"struct\",\"fields\":[{\"name\":\"ab\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}}]},\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_prims\",\"type\":{\"type\":\"map\",\"keyType\":\"integer\",\"valueType\":\"long\",\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_rows\",\"type\":{\"type\":\"map\",\"keyType\":\"integer\",\"valueType\":{\"type\":\"struct\",\"fields\":[{\"name\":\"ab\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}}]},\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_arrays\",\"type\":{\"type\":\"map\",\"keyType\":\"long\",\"valueType\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}}]}","partitionColumns":[],"configuration":{},"createdTime":1713368421437}}
+{"commitInfo":{"timestamp":1715358308005,"operation":"WRITE","operationParameters":{"mode":"Append","partitionBy":"[]"},"isolationLevel":"Serializable","isBlindAppend":true,"operationMetrics":{"numFiles":"1","numOutputRows":"200","numOutputBytes":"21057"},"engineInfo":"Apache-Spark/3.5.0 Delta-Lake/3.2.0-SNAPSHOT","txnId":"c84f1a78-0895-4f01-b00e-f3a984c8afca"}}
+{"metaData":{"id":"ab49cd9e-a908-4aad-a15b-9dd117d3e0ab","format":{"provider":"parquet","options":{}},"schemaString":"{\"type\":\"struct\",\"fields\":[{\"name\":\"ByteType\",\"type\":\"byte\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ShortType\",\"type\":\"short\",\"nullable\":true,\"metadata\":{}},{\"name\":\"IntegerType\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}},{\"name\":\"LongType\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}},{\"name\":\"FloatType\",\"type\":\"float\",\"nullable\":true,\"metadata\":{}},{\"name\":\"DoubleType\",\"type\":\"double\",\"nullable\":true,\"metadata\":{}},{\"name\":\"decimal\",\"type\":\"decimal(10,2)\",\"nullable\":true,\"metadata\":{}},{\"name\":\"BooleanType\",\"type\":\"boolean\",\"nullable\":true,\"metadata\":{}},{\"name\":\"StringType\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"BinaryType\",\"type\":\"binary\",\"nullable\":true,\"metadata\":{}},{\"name\":\"DateType\",\"type\":\"date\",\"nullable\":true,\"metadata\":{}},{\"name\":\"TimestampType\",\"type\":\"timestamp\",\"nullable\":true,\"metadata\":{}},{\"name\":\"TimestampNTZType\",\"type\":\"timestamp_ntz\",\"nullable\":true,\"metadata\":{}},{\"name\":\"nested_struct\",\"type\":{\"type\":\"struct\",\"fields\":[{\"name\":\"aa\",\"type\":\"string\",\"nullable\":true,\"metadata\":{}},{\"name\":\"ac\",\"type\":{\"type\":\"struct\",\"fields\":[{\"name\":\"aca\",\"type\":\"integer\",\"nullable\":true,\"metadata\":{}}]},\"nullable\":true,\"metadata\":{}}]},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_prims\",\"type\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_arrays\",\"type\":{\"type\":\"array\",\"elementType\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"array_of_structs\",\"type\":{\"type\":\"array\",\"elementType\":{\"type\":\"struct\",\"fields\":[{\"name\":\"ab\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}}]},\"containsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_prims\",\"type\":{\"type\":\"map\",\"keyType\":\"integer\",\"valueType\":\"long\",\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_rows\",\"type\":{\"type\":\"map\",\"keyType\":\"integer\",\"valueType\":{\"type\":\"struct\",\"fields\":[{\"name\":\"ab\",\"type\":\"long\",\"nullable\":true,\"metadata\":{}}]},\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}},{\"name\":\"map_of_arrays\",\"type\":{\"type\":\"map\",\"keyType\":\"long\",\"valueType\":{\"type\":\"array\",\"elementType\":\"integer\",\"containsNull\":true},\"valueContainsNull\":true},\"nullable\":true,\"metadata\":{}}]}","partitionColumns":[],"configuration":{},"createdTime":1715358307675}}
 {"protocol":{"minReaderVersion":3,"minWriterVersion":7,"readerFeatures":["timestampNtz"],"writerFeatures":["timestampNtz"]}}
-{"add":{"path":"part-00000-981a72ea-9b1a-4bf3-8c3c-3d7e56a7bb45-c000.snappy.parquet","partitionValues":{},"size":30312,"modificationTime":1713368423449,"dataChange":true,"stats":"{\"numRecords\":200,\"minValues\":{\"ByteType\":-128,\"ShortType\":1,\"IntegerType\":1,\"LongType\":2,\"FloatType\":0.234,\"DoubleType\":234234.23,\"decimal\":123.52,\"StringType\":\"1\",\"DateType\":\"1970-01-01\",\"TimestampType\":\"1970-01-01T06:30:23.523Z\",\"TimestampNTZType\":\"1970-01-03T17:03:54.000\",\"nested_struct\":{\"aa\":\"1\",\"ac\":{\"aca\":1}}},\"maxValues\":{\"ByteType\":127,\"ShortType\":199,\"IntegerType\":199,\"LongType\":200,\"FloatType\":46.566,\"DoubleType\":4.661261177E7,\"decimal\":24580.48,\"StringType\":\"99\",\"DateType\":\"1970-02-16\",\"TimestampType\":\"1970-02-23T22:48:01.077Z\",\"TimestampNTZType\":\"1971-06-24T11:56:06.000\",\"nested_struct\":{\"aa\":\"99\",\"ac\":{\"aca\":199}}},\"nullCount\":{\"ByteType\":3,\"ShortType\":4,\"IntegerType\":9,\"LongType\":8,\"FloatType\":8,\"DoubleType\":4,\"decimal\":3,\"BooleanType\":3,\"StringType\":4,\"BinaryType\":4,\"DateType\":4,\"TimestampType\":4,\"TimestampNTZType\":3,\"nested_struct\":{\"aa\":14,\"ac\":{\"aca\":22}},\"array_of_prims\":8,\"array_of_arrays\":25,\"array_of_structs\":0,\"map_of_prims\":8,\"map_of_rows\":0,\"map_of_arrays\":7}}"}}
+{"add":{"path":"part-00000-bf6680d4-5e83-4fce-8ebb-d2b60d7e69c9-c000.snappy.parquet","partitionValues":{},"size":21057,"modificationTime":1715358307997,"dataChange":true,"stats":"{\"numRecords\":200,\"minValues\":{\"ByteType\":-128,\"ShortType\":1,\"IntegerType\":1,\"LongType\":2,\"FloatType\":0.234,\"DoubleType\":234234.23,\"decimal\":123.52,\"StringType\":\"1\",\"DateType\":\"1970-01-01\",\"TimestampType\":\"1970-01-01T06:30:23.523Z\",\"TimestampNTZType\":\"1970-01-03T17:03:54.000\",\"nested_struct\":{\"aa\":\"1\",\"ac\":{\"aca\":1}}},\"maxValues\":{\"ByteType\":127,\"ShortType\":199,\"IntegerType\":199,\"LongType\":200,\"FloatType\":46.566,\"DoubleType\":4.661261177E7,\"decimal\":24580.48,\"StringType\":\"99\",\"DateType\":\"1970-02-16\",\"TimestampType\":\"1970-02-23T22:48:01.077Z\",\"TimestampNTZType\":\"1971-06-24T11:56:06.000\",\"nested_struct\":{\"aa\":\"99\",\"ac\":{\"aca\":199}}},\"nullCount\":{\"ByteType\":3,\"ShortType\":4,\"IntegerType\":9,\"LongType\":8,\"FloatType\":8,\"DoubleType\":4,\"decimal\":3,\"BooleanType\":3,\"StringType\":4,\"BinaryType\":4,\"DateType\":4,\"TimestampType\":4,\"TimestampNTZType\":3,\"nested_struct\":{\"aa\":14,\"ac\":{\"aca\":22}},\"array_of_prims\":200,\"array_of_arrays\":200,\"array_of_structs\":200,\"map_of_prims\":200,\"map_of_rows\":200,\"map_of_arrays\":200}}"}}

connectors/golden-tables/src/test/scala/io/delta/golden/GoldenTables.scala

@@ -1038,7 +1038,18 @@ class GoldenTables extends QueryTest with SharedSparkSession {
     writeBasicTimestampTable(tablePath, TimeZone.getTimeZone("PST"))
   }
 
+  generateGoldenTable("parquet-all-types-legacy-format") { tablePath =>
+    withSQLConf(("spark.sql.parquet.writeLegacyFormat", "true")) {
+      generateAllTypesTable(tablePath)
+    }
+  }
+
   generateGoldenTable("parquet-all-types") { tablePath =>
+    // generating using the standard parquet format
+    generateAllTypesTable(tablePath)
+  }
+
+  def generateAllTypesTable(tablePath: String): Unit = {
     val timeZone = java.util.TimeZone.getTimeZone("UTC")
     java.util.TimeZone.setDefault(timeZone)
     import java.sql._
@@ -1113,6 +1124,7 @@ class GoldenTables extends QueryTest with SharedSparkSession {
         if (i % 61 != 0) new java.sql.Date(i * 20000000L) else null,
         if (i % 62 != 0) new Timestamp(i * 23423523L) else null,
         if (i % 69 != 0) LocalDateTime.ofEpochSecond(i * 234234L, 200012, UTC) else null,
+        // nested_struct
         if (i % 63 != 0) {
           if (i % 19 == 0) {
             // write a struct with all fields null
@@ -1121,13 +1133,15 @@ class GoldenTables extends QueryTest with SharedSparkSession {
             Row(i.toString, if (i % 23 != 0) Row(i) else null)
           }
         } else null,
+        // array_of_prims
         if (i % 25 != 0) {
           if (i % 29 == 0) {
             scala.Array()
           } else {
             scala.Array(i, null, i + 1)
           }
         } else null,
+        // array_of_arrays
         if (i % 8 != 0) {
           val singleElemArray = scala.Array(i)
           val doubleElemArray = scala.Array(i + 10, i + 20)
@@ -1144,7 +1158,11 @@ class GoldenTables extends QueryTest with SharedSparkSession {
             case 6 => scala.Array()
           }
         } else null,
-        scala.Array(Row(i.longValue()), null),
+        // array_of_structs
+        if (i % 10 != 0) {
+          scala.Array(Row(i.longValue()), null)
+        } else null,
+        // map_of_prims
         if (i % 28 != 0) {
           if (i % 30 == 0) {
             Map()
@@ -1155,7 +1173,11 @@ class GoldenTables extends QueryTest with SharedSparkSession {
             )
           }
         } else null,
-        Map(i + 1 -> (if (i % 10 == 0) Row((i * 20).longValue()) else null)),
+        // map_of_rows
+        if (i % 25 != 0) {
+          Map(i + 1 -> (if (i % 10 == 0) Row((i * 20).longValue()) else null))
+        } else null,
+        // map_of_arrays
         if (i % 30 != 0) {
           if (i % 24 == 0) {
             Map()
@@ -1181,7 +1203,6 @@ class GoldenTables extends QueryTest with SharedSparkSession {
       .save(tablePath)
   }
 
-
   def writeBasicDecimalTable(tablePath: String): Unit = {
     val data = Seq(
       Seq("234", "1", "2", "3"),

kernel/kernel-defaults/src/main/java/io/delta/kernel/defaults/internal/parquet/ArrayColumnReader.java

@@ -19,10 +19,13 @@
 
 import org.apache.parquet.io.api.Converter;
 import org.apache.parquet.schema.GroupType;
+import org.apache.parquet.schema.Type;
 
 import io.delta.kernel.data.ColumnVector;
 import io.delta.kernel.types.ArrayType;
 
+import static io.delta.kernel.internal.util.Preconditions.checkArgument;
+
 import io.delta.kernel.defaults.internal.data.vector.DefaultArrayVector;
 import static io.delta.kernel.defaults.internal.parquet.ParquetColumnReaders.createConverter;
 
@@ -52,15 +55,38 @@ public ColumnVector getDataColumnVector(int batchSize) {
         return arrayVector;
     }
 
+    /**
+     * Currently, support for 3-level nested arrays only.
+     * <p>
+     * optional group readerFeatures (LIST) {
+     *   repeated group list {
+     *     optional binary element (STRING);
+     *   }
+     * }
+     * <p>
+     * optional group readerFeatures (LIST) {
+     *   repeated group bag {
+     *     optional binary array (STRING);
+     *   }
+     * }
+     *
+     * TODO: Add support for 2-level nested arrays.
+     */
     private static Converter createElementConverter(
         int initialBatchSize,
         ArrayType typeFromClient,
         GroupType typeFromFile) {
 
-        final GroupType innerElementType = (GroupType) typeFromFile.getType("list");
-        return createConverter(
-            initialBatchSize,
-            typeFromClient.getElementType(),
-            innerElementType.getType("element"));
+        checkArgument(
+                typeFromFile.getFieldCount() == 1, "Expected exactly one field in the array type");
+        GroupType repeatedGroup = typeFromFile.getType(0).asGroupType();
+
+        // TODO: handle the legacy 2-level list physical format
+        checkArgument(repeatedGroup.getFieldCount() == 1,
+                "Expected exactly one field in the repeated group");
+
+        Type elmentType = repeatedGroup.getType(0);
+
+        return createConverter(initialBatchSize, typeFromClient.getElementType(), elmentType);
     }
 }