diff --git a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java
index 06cd9ea2d242c..de5b2e820a50d 100644
--- a/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java
+++ b/sql/core/src/main/java/org/apache/spark/sql/execution/datasources/parquet/SpecificParquetRecordReaderBase.java
@@ -107,7 +107,16 @@ public void initialize(InputSplit inputSplit, TaskAttemptContext taskAttemptCont
       footer = readFooter(configuration, file, range(split.getStart(), split.getEnd()));
       MessageType fileSchema = footer.getFileMetaData().getSchema();
       FilterCompat.Filter filter = getFilter(configuration);
-      blocks = filterRowGroups(filter, footer.getBlocks(), fileSchema);
+      try {
+        blocks = filterRowGroups(filter, footer.getBlocks(), fileSchema);
+      } catch (IllegalArgumentException e) {
+        // In the case where a particular parquet files does not contain
+        // the column(s) in the filter, we don't do filtering at this level
+        // PARQUET-389 will resolve this issue in Parquet 1.9, which may be used
+        // by future Spark versions. This is a workaround for current Spark version.
+        // Also the assumption here is that the predicates will be applied later
+        blocks = footer.getBlocks();
+      }
     } else {
       // otherwise we find the row groups that were selected on the client
       footer = readFooter(configuration, file, NO_FILTER);
diff --git a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
index a0d57d79f045a..6fdd0621050b7 100644
--- a/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
+++ b/sql/core/src/test/scala/org/apache/spark/sql/execution/datasources/parquet/ParquetFilterSuite.scala
@@ -578,4 +578,66 @@ class ParquetFilterSuite extends QueryTest with ParquetTest with SharedSQLContex
       // scalastyle:on nonascii
     }
   }
+
+  test("SPARK-18539 - filtered by non-existing parquet column") {
+    Seq("parquet").foreach { format =>
+      withSQLConf(SQLConf.PARQUET_FILTER_PUSHDOWN_ENABLED.key -> "true") {
+        withTempPath { path =>
+          import testImplicits._
+          Seq((1, "abc"), (2, "hello")).toDF("a", "b").write.format(format).save(path.toString)
+
+          // user-specified schema contains nonexistent columns
+          val schema = StructType(
+            Seq(StructField("a", IntegerType),
+              StructField("b", StringType),
+              StructField("c", IntegerType)))
+          val readDf1 = spark.read.schema(schema).format(format).load(path.toString)
+
+          // Read the table without any filter
+          checkAnswer(readDf1, Row(1, "abc", null) :: Row(2, "hello", null) :: Nil)
+          // Read the table with a filter on existing columns
+          checkAnswer(readDf1.filter("a < 2"), Row(1, "abc", null) :: Nil)
+
+          // Read the table with a filter on nonexistent columns
+          checkAnswer(readDf1.filter("c < 2"), Nil)
+          checkAnswer(readDf1.filter("c is not null"), Nil)
+
+          checkAnswer(readDf1.filter("c is null"),
+            Row(1, "abc", null) :: Row(2, "hello", null) :: Nil)
+
+          checkAnswer(readDf1.filter("c is null and a < 2"),
+            Row(1, "abc", null) :: Nil)
+
+          // With another parquet file that contains the column "c"
+          Seq((2, "abc", 3), (3, "hello", 4)).toDF("a", "b", "c")
+            .write.format(format).mode(SaveMode.Append).save(path.toString)
+
+          // Right now, there are 2 parquet files. one with the column "c",
+          // the other does not have it.
+          val readDf2 = spark.read.schema(schema).format(format).load(path.toString)
+          // Read the table without any filter
+          checkAnswer(readDf2,
+            Row(1, "abc", null) :: Row(2, "hello", null) ::
+            Row(2, "abc", 3) :: Row(3, "hello", 4) :: Nil)
+
+          // Read the table with a filter on existing columns
+          checkAnswer(readDf2.filter("a < 2"), Row(1, "abc", null) :: Nil)
+
+          // column "c" is in one parquet file, not in the other parquet file
+          checkAnswer(readDf2.filter("c < 4"),
+            Row(2, "abc", 3) :: Nil)
+          checkAnswer(readDf2.filter("c is not null"),
+            Row(2, "abc", 3) :: Row(3, "hello", 4) :: Nil)
+
+          checkAnswer(readDf2.filter("c is null"),
+            Row(1, "abc", null) :: Row(2, "hello", null) :: Nil)
+
+          checkAnswer(readDf2.filter("c is null and a < 2"),
+            Row(1, "abc", null) :: Nil)
+
+          readDf2.filter("c is null and a < 2").explain(true)
+        }
+      }
+    }
+  }
 }