修改首页流量统计中addrTypes,transTypes,entranceIds为默认值,避免每次从数据库中查询效率低的问题
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@@ -216,8 +216,6 @@ public class DashboardServiceController extends BaseRestController {
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@RequestMapping(value = "trafficBandwidthTransThree", method = RequestMethod.GET)
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@ApiOperation(value = "带宽根据ip46,协议tcp,udp查询详情", httpMethod = "GET", notes = "对应带宽根据IPv4,6,协议tcp,udp统计数据显示")
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public Map<String,?> trafficBandwidthTransThree(String beginDate,String endDate,String searchQuotaType,Model model, HttpServletRequest request, HttpServletResponse response) {
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String[] addrTypes=dashboardService.getFiledTypeByName("addr_type");
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String[] transTypes=dashboardService.getFiledTypeByName("trans_type");
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long start = System.currentTimeMillis();
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AuditLogThread auditLogThread = super.saveRequestLog(servicesRequestLogService, Constants.OPACTION_GET, request, null);
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Map resultMap=new HashMap();
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@@ -66,7 +66,14 @@ public class DashboardService extends BaseService {
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public NtcTotalReportDao ntcTotalReportDao;
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@Autowired
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public TrafficPortActiveStatisticDao trafficPortActiveStatisticDao;
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//ip地址类型
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private final String[] addrTypes = {"4","6"} ;
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//tcp udp
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private final String[] transTypes ={"17","6"} ;
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//区域
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private final String[] entranceIds ={"1","2"} ;
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/**
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* 流量统计 数据显示 info:先查询最近时间,根据时间条件查询数据 效率提高
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*/
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@@ -1285,9 +1292,6 @@ public class DashboardService extends BaseService {
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dateRangeList.add(calendar.getTime());
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calendar.add(Calendar.MINUTE, Constants.TREND_TIME_INTERVAL);
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}
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String[] addrTypes = getFiledTypeByName("addr_type");
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String[] transTypes = getFiledTypeByName("trans_type");
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String[] entranceIds = getFiledTypeByName("entrance_id");
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if (bandwidthListIPvx != null && bandwidthListIPvx.size() > 0 && bandwidthListProtocol != null
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&& bandwidthListProtocol.size() > 0 && addrTypes != null && addrTypes.length > 0
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&& transTypes != null && transTypes.length > 0 && entranceIds != null && entranceIds.length > 0) {
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