1113. Integer Set Partition

针对一组正整数,本篇介绍一种算法实现:将其划分为两个互斥子集,目标首先是使两子集元素数量之差最小,其次是在此基础上使两子集元素总和之差尽可能大。文中提供了一个具体的C++实现方案。

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1113. Integer Set Partition (25)

时间限制
150 ms
内存限制
65536 kB
代码长度限制
16000 B
判题程序
Standard
作者
CHEN, Yue

Given a set of N (> 1) positive integers, you are supposed to partition them into two disjoint sets A1 and A2 of n1 and n2 numbers, respectively. Let S1 and S2 denote the sums of all the numbers in A1 and A2, respectively. You are supposed to make the partition so that |n1 - n2| is minimized first, and then |S1 - S2| is maximized.

Input Specification:

Each input file contains one test case. For each case, the first line gives an integer N (2 <= N <= 105), and then N positive integers follow in the next line, separated by spaces. It is guaranteed that all the integers and their sum are less than 231.

Output Specification:

For each case, print in a line two numbers: |n1 - n2| and |S1 - S2|, separated by exactly one space.

Sample Input 1:
10
23 8 10 99 46 2333 46 1 666 555
Sample Output 1:
0 3611
Sample Input 2:
13
110 79 218 69 3721 100 29 135 2 6 13 5188 85
Sample Output 2:
1 9359
这个题很直白。
#include<iostream>
#include<vector>
#include<algorithm>

using namespace std;

int a[100000];
int main()
{
	int n;
	cin>>n;
	int s1=0,s2=0;
	for(int i=0;i<n;i++)
		cin>>a[i];
	sort(a,a+n);
		for(int i=0;i<n/2;i++)
			s1+=a[i];
		for(int i=n/2;i<n;i++)
			s2+=a[i];
	if(n%2==0)
		cout<<"0 ";
	else
		cout<<"1 ";
	cout<<s2-s1;
}


robotframework给spark-shell写测试用例,spark-shell的开启方式为: (1)cd /opt/module/ume/spark/bin (2)./spark-shell --master local --conf spark.hadoop.hive.metastore.uris=thrift://local:19083 spark-shell的建表语句为: import org.apache.iceberg.Schema; import org.apache.iceberg.types.Types; //创建schema val schema = new Schema( Types.NestedField.required(1, "level", Types.StringType.get()), Types.NestedField.required(2, "event_time", Types.TimestampType.withoutZone()), //without Zone Types.NestedField.required(3, "message", Types.StringType.get()), Types.NestedField.required(4, "count", Types.IntegerType.get()) ); import org.apache.iceberg.PartitionSpec; //创建分区 val spec = PartitionSpec.builderFor(schema).hour("event_time").gpHash("level", 2).build(); import org.apache.iceberg.hive.HiveCatalog; //创建catalog val catalog = new HiveCatalog(); catalog.setConf(spark.sparkContext.hadoopConfiguration); val properties = Map("warehouse"->"hdfs://node199:9000/user/spark","uri"->"thrift://localhost:19083"); import collection.JavaConversions._ catalog.initialize("hive",mapAsJavaMap(properties)); // 创建数据库,如果spark中此数据库已经存在则可以忽略 import org.apache.iceberg.catalog.Namespace val namespace = Namespace.of("postgres"); import org.apache.iceberg.relocated.com.google.common.collect.ImmutableMap catalog.createNamespace(namespace, ImmutableMap.of()); //创建数据表 import org.apache.iceberg.Table; import org.apache.iceberg.catalog.TableIdentifier; val name = TableIdentifier.of("postgres", "test_ts_without_zone"); val table = catalog.createTable(name, schema, spec); 核心是通过robotframework,通过writer语句,要解决robotframework与spark-shell的交互问题
最新发布
03-15
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