diff --git a/src/parquet/ReadParquet.cpp b/src/parquet/ReadParquet.cpp
index 244276d1b1..5eac6a1a81 100644
--- a/src/parquet/ReadParquet.cpp
+++ b/src/parquet/ReadParquet.cpp
@@ -1,12 +1,14 @@
 #include "ReadParquet.h"
 #include "UtilParquet.h"
 
+// Returns the number of elements read
 template <typename ReaderType, typename ChplType>
 int64_t readColumn(void* chpl_arr, int64_t startIdx, std::shared_ptr<parquet::ColumnReader> column_reader,
                 bool hasNonFloatNulls, int64_t i, int64_t numElems, int64_t batchSize,
                 int64_t values_read, bool* where_null_chpl) {
   int16_t definition_level; // nullable type and only reading single records in batch
   auto chpl_ptr = (ChplType*)chpl_arr;
+  int64_t num_read = 0;
   ReaderType* reader =
     static_cast<ReaderType*>(column_reader.get());
   startIdx -= reader->Skip(startIdx);
@@ -17,6 +19,7 @@ int64_t readColumn(void* chpl_arr, int64_t startIdx, std::shared_ptr<parquet::Co
         batchSize = numElems - i;
       (void)reader->ReadBatch(batchSize, nullptr, nullptr, &chpl_ptr[i], &values_read);
       i+=values_read;
+      num_read += values_read;
     }
   }
   else {
@@ -27,9 +30,10 @@ int64_t readColumn(void* chpl_arr, int64_t startIdx, std::shared_ptr<parquet::Co
         where_null_chpl[i] = true;
       }
       i++;
+      num_read++;
     }
   }
-  return i;
+  return num_read;
 }
 
 template <typename ReaderType, typename ChplType, typename PqType>
@@ -38,6 +42,7 @@ int64_t readColumnDbFl(void* chpl_arr, int64_t startIdx, std::shared_ptr<parquet
                     int64_t values_read, bool* where_null_chpl) {
   int16_t definition_level; // nullable type and only reading single records in batch
   auto chpl_ptr = (ChplType*)chpl_arr;
+  int64_t num_read = 0;
   ReaderType* reader =
     static_cast<ReaderType*>(column_reader.get());
   startIdx -= reader->Skip(startIdx);
@@ -53,8 +58,10 @@ int64_t readColumnDbFl(void* chpl_arr, int64_t startIdx, std::shared_ptr<parquet
       chpl_ptr[i] = NAN;
     }
     i++;
+    num_read++;
   }
-  return i;
+  //return i;
+  return num_read;
 }
 
 template <typename ReaderType, typename ChplType, typename PqType>
@@ -174,7 +181,7 @@ int cpp_readStrColumnByName(const char* filename, void* chpl_arr, const char* co
 int cpp_readColumnByName(const char* filename, void* chpl_arr, bool* where_null_chpl, const char* colname, int64_t numElems, int64_t startIdx, int64_t batchSize, int64_t byteLength, bool hasNonFloatNulls, char** errMsg) {
   try {
     int64_t ty = cpp_getType(filename, colname, errMsg);
-  
+
     std::unique_ptr<parquet::ParquetFileReader> parquet_reader =
       parquet::ParquetFileReader::OpenFile(filename, false);
 
@@ -182,7 +189,7 @@ int cpp_readColumnByName(const char* filename, void* chpl_arr, bool* where_null_
     int num_row_groups = file_metadata->num_row_groups();
 
     int64_t i = 0;
-    for (int r = 0; r < num_row_groups; r++) {
+    for (int r = 0; (r < num_row_groups) && (i < numElems); r++) {
       std::shared_ptr<parquet::RowGroupReader> row_group_reader =
         parquet_reader->RowGroup(r);
 
@@ -191,7 +198,6 @@ int cpp_readColumnByName(const char* filename, void* chpl_arr, bool* where_null_
       std::shared_ptr<parquet::ColumnReader> column_reader;
 
       auto idx = file_metadata -> schema() -> ColumnIndex(colname);
-      auto max_def = file_metadata -> schema() -> Column(idx) -> max_definition_level(); // needed to determine if nulls are allowed
 
       if(idx < 0) {
         std::string dname(colname);
@@ -200,6 +206,7 @@ int cpp_readColumnByName(const char* filename, void* chpl_arr, bool* where_null_
         *errMsg = strdup(msg.c_str());
         return ARROWERROR;
       }
+      auto max_def = file_metadata -> schema() -> Column(idx) -> max_definition_level(); // needed to determine if nulls are allowed
       
       column_reader = row_group_reader->Column(idx);
 
diff --git a/tests/io_test.py b/tests/io_test.py
index c1c9cfb7ed..beddce5882 100644
--- a/tests/io_test.py
+++ b/tests/io_test.py
@@ -317,6 +317,31 @@ def test_edge_case_read_write(self, par_test_base_tmp, dtype, comp):
             else:
                 assert (np_edge_case == pq_arr.to_ndarray()).all()
 
+    @pytest.mark.parametrize("prob_size", pytest.prob_size)
+    def test_large_parquet_io(self,par_test_base_tmp,prob_size) :
+
+        with tempfile.TemporaryDirectory(dir=par_test_base_tmp) as tmp_dirname:
+            filename = f"{tmp_dirname}/pq_test_large_parquet"
+            size = 2**21 + 8  # A problem had been detected with parquet files of > 2**21 entries
+            bool_array = np.array((size//2)*[True,False]).tolist()
+            flt_array  = np.arange(size).astype(np.float64).tolist()
+            int_array  = np.arange(size).astype(np.int64).tolist()
+            str_array  = np.array(["a"+str(i) for i in np.arange(size)]).tolist()
+            arrays = [bool_array, int_array, flt_array, str_array]
+            tuples = list(zip(*arrays))
+            names = ['first','second','third','fourth']
+            index = pd.MultiIndex.from_tuples(tuples,names=names)
+            s = pd.Series(np.random.randn(size),index=index)
+            df = s.to_frame()
+            df.to_parquet(filename)
+            ak_df = ak.DataFrame(ak.read_parquet(filename)) 
+            #  This check is on all of the random numbers generated in s
+            assert np.all(ak_df.to_pandas().values[:,0] == s.values)
+            #  This check is on all of the elements of the MultiIndex
+            for i in range(len(names)) :
+                assert np.all( df.index.get_level_values(names[i]).to_numpy() == ak_df[names[i]].to_ndarray() )
+                
+
     @pytest.mark.parametrize("dtype", NUMERIC_AND_STR_TYPES)
     def test_get_datasets(self, par_test_base_tmp, dtype):
         ak_arr = make_ak_arrays(10, dtype)