IgniteSpark integration forget to close the IgniteContext and stops the client node in case if error during PairFunction logic

public class Example {
    public static void main(String[] args) {
        String configPath = "/home/andrei/BDP/big-data-accelerator/modules/gridgain-spark-loader-examples/config/client.xml";
        IgniteSparkSession igniteSession = IgniteSparkSession.builder()
                .appName("Spark Ignite catalog example")
                .master("local")
                .config("ignite.disableSparkSQLOptimization", true)
                .igniteConfig(configPath)
                .getOrCreate();
        JavaSparkContext sparkCtx = new JavaSparkContext(igniteSession.sparkContext());
        final JavaRDD<Row> records = sparkCtx.parallelize(Arrays.asList(
                new GenericRow()
        ));
        JavaPairRDD<Integer, Integer> rdd_records = records.mapToPair(new PairFunction<Row, Integer, Integer>() {
            @Override
            public Tuple2<Integer, Integer> call(Row row) throws Exception {
                throw new IllegalStateException("some error");
            }
        });
        JavaIgniteContext<Integer, Integer> igniteContext = new JavaIgniteContext<>(sparkCtx, configPath);
        JavaIgniteRDD<Integer, Integer> igniteRdd = igniteContext.<Integer, Integer>fromCache("Person");
        igniteRdd.savePairs(rdd_records);
        igniteContext.close(true);
    }
}

Looks like next internal code (saveValues method)should also close the IgniteContext in case of an unexpected exception, not only data streamer:

try {
     it.foreach(value ⇒

{          val key = affinityKeyFunc(value, node.orNull)           streamer.addData(key, value)        }

)
     }
     finally

{         streamer.close()     }

})
 }