Kontinuation

21/09/18 11:51:31 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Using Spark's default log4j profile: org/apache/spark/log4j-defaults.properties
21/09/18 11:51:31 INFO SparkContext: Running Spark version 3.1.2
21/09/18 11:51:31 INFO ResourceUtils: ==============================================================
21/09/18 11:51:31 INFO ResourceUtils: No custom resources configured for spark.driver.
21/09/18 11:51:31 INFO ResourceUtils: ==============================================================
21/09/18 11:51:31 INFO SparkContext: Submitted application: SedonaSQL-demo
21/09/18 11:51:31 INFO ResourceProfile: Default ResourceProfile created, executor resources: Map(cores -> name: cores, amount: 1, script: , vendor: , memory -> name: memory, amount: 1024, script: , vendor: , offHeap -> name: offHeap, amount: 0, script: , vendor: ), task resources: Map(cpus -> name: cpus, amount: 1.0)
21/09/18 11:51:31 INFO ResourceProfile: Limiting reso

Kontinuation

#include <iostream>
#include "metalang.hpp"

struct I {
        template <typename x, typename _0>
        struct apply {
                typedef x value;
        };
};

Kontinuation

#include <iostream>
#include <functional>

using namespace std;


template<typename _CAR,typename _CDR>
pair<_CAR,_CDR> cons(_CAR car,_CDR cdr)
{
        return std::make_pair(car,cdr);

Kontinuation

#include <iostream>
#include <functional>

using namespace std;


template <typename ... _> struct extend;
template <typename t_ret, typename ... t_args, typename ... t_arge>
struct extend <t_ret(t_args ...) , t_arge ...> {
        static std::function<t_ret(t_args ..., t_arge ...)> impl (std::function<t_ret(t_args ...)> f) {