Bloom filter-based xml packets filtering for millions of path queries

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鲲鹏应用开发考试(试卷编号131)

鲲鹏应用开发考试(试卷编号131)1.[单选题]关于镜像和容器的描述,以下哪项是不正确的?A)容器是动态的,可用容器来运行应用B)镜像是只读的, 可以理解为静态文件C)容器是由镜像实例化而来的D)容器不能拥有root权限,否则很不安全答案:D解析:2.[单选题]CPU Core 访问服务器上不同位[的内存时,内存访问延迟从高到低排序正确的是?A)跨Socket >跨NUMA不跨Socket > NUMA内B)NUMA内>跨NUMA不跨Socket >跨SocketC)跨NUMA不跨Socket >跨Socket > NUMA内D)跨Socket > NUMA内>跨NUMA不跨Socket答案:A解析:3.[单选题]在rpmbuli d的SPEC目录下,spec配置文件中用于将软件构建成机器代码(对于编译语言)或者字节代码的(对于解释性语言)命令是哪个?A)%filesB)%buildC)%installD)%clean答案:B解析:4.[单选题]为云开源镜像仓库中的依赖包更新周期间隔多久A)每月更新一次B)每周更新一次C)每年更新一次D)每天会随官方发布的版本进行更新答案:D解析:5.[单选题]通过华为鯤鹏性能优化工具对C/C++应用程序进行性能分析时，分析结果不包括的是？A)各个函数性能指标数据统计，以及函数代码映射信息B)任务执行时间、指令数、时钟周期、IPC等总体性能指标统计C)热点函数识别，以及函数火焰图解析:6.[单选题]Kunpeng920加速引擎不包括下列哪个？A)压缩加速引擎B)SSL加速引擎C)加密算法加速引擎D)重删加速引擎答案:D解析:7.[单选题]性能分析任务执行完成后,以下哪项是分析结果中无法查看到的?A)针对Top热点函数的性能优化建议B)函数火焰图C)Top 10热点函数性能指标数据D)分析过程中的采集日志答案:A解析:8.[单选题]GCC 升级../configure 命令后面的配置项哪一条是错误的是（）A)--enable-checking=releaseB)--enable-languages=c,c++C)--disable-multilibD)--initialize-insecure答案:D解析:9.[单选题]以下哪个不是大数据的组件?A)ZookeeperB)KafkaC)StormD)Mariadb答案:D解析:10.[单选题]华为在哪一年拥有 ARMv8 架构的永久授权？（）A)2013B)2016C)2015D)2017答案:B11.[单选题]鲲鹏处理器包含计算、存储、设备I0、中断以及虚拟化等子系统,这些子系统通过以下哪种方式互联?A)PCIe 4. 0网卡B)南桥控制器C)DDR4通道D)高速内部总线答案:D解析:12.[单选题]Docker是目前容器技术领域最热门的开源项目，下面哪项不属于Docker的基本概念？A)RepositoryB)ImageC)DeploymentD)Volume答案:C解析:13.[单选题]在鲲鹏平台中进行编译时,定义编译生成的应用程序为 64 位使用的参数是什么?A)-m32B)-mabi=1p64C)-mabi=1p32D)-m64答案:B解析:14.[单选题]使用Kunpeng Tuning kit鲲鹏性能优化工具做锁与等待分析时，是基于以下哪个工具采样的数据?A)sysbench的采样数据B)ab的采样数据C)WebBench的采样数据D)perf的采样数据答案:D解析:Tuning kit的进程线程性能分析：锁与等待分析，基于linux perf工具的采样数据。

1+x网络安全评估测试题库与答案

1+x网络安全评估测试题库与答案1、（单选题） Windows操作系统中查看ARP缓存表的命令是（）。

（2分）A、arp -aB、arp -dC、arp -sD、arp -n答案：A2、（单选题）密码使用的场景通讯类不包括下列哪个？（10分）A、 QQB、微信C、陌陌D、购物账户答案：D3、（单选题） Burp的Intruder模块中，哪种模式只使用一个payload，每次替换所有位置？（10分）A、SniperB、Battering ramC、PitchforkD、Cluster bomb答案：B4、（单选题）以下哪种攻击不能获取用户的会话标识？（10分）A、 SQL注入B、 XSSC、会话凭证D、凭证预测答案：A5、（判断题）一个高级用户可以访问低级用户信息是向上越权（10分）A、正确B、错误答案：B6、（单选题）《网络安全法》规定，网络运营者应当制定（），及时处置系统漏洞计算机病毒网络攻击网络侵入等安全风险。

（10分）A、网络安全事件应急预案B、网络安全事件补救措施C、网络安全事件应急演练方案D、网站安全规章制度答案：A7、（单选题）文件包含漏洞的一般特征不包含（2分）A、?page=a.phpB、?home=a.htmlC、?file=contentD、?id=1’答案：D8、（判断题） TCP/IP是7层模型（10分）A、正确B、错误答案：B9、（单选题）下面哪个函数可以起到过滤作用？（10分）A、replaceB、preg_replaceC、addslashesD、find答案：B10、（单选题） AWVS是一款什么用途的渗透测试工具（）。

（2分）A、漏洞扫描B、SQL注入C、XSS攻击D、暴力破解答案：A11、（单选题）故意制作、传播计算机病毒等破坏性程序，影响计算机系统正常运行，后果严重的，将受到什么处罚？（2分）A、处五年以下有期徒刑或者拘役B、拘留C、罚款D、警告答案：A12、（单选题）（）可以被Apache解析成php文件（2分）A、1.php.333B、1.php.htmlC、1.jpg%00.phpD、1.php2.html答案：A13、（单选题）会话固定的原理是？（10分）A、截取目标登录凭证B、预测对方登录可能用到的凭证C、让目标误以为攻击者是服务器D、让目标使用自己构造好的凭证登录答案：D14、（单选题） UDP协议工作在TCP/IP的哪一层?（10分）A、传输层B、网络层C、物理层D、应用层答案：A15、（单选题）路由器是工作在以下哪一层的设备？（10分）A、物理层B、链路层C、网络层D、传输层答案：C16、（判断题） Sqlmap是一款强有力的注入工具（10分）A、正确B、错误答案：A17、（单选题） Linux系统中，查看当前最后一次执行的命令的返回状态，使用以下哪个命令？（2分）A、$*B、$@C、$?D、$!答案：C18、（单选题） TCP协议采用以下哪种包用于确认数据?（10分）A、RSTB、FINC、ACKD、SYN答案：C19、（判断题）被扫描的主机是不会主动联系扫描主机的，所以被动扫描只能通过截获网络上散落的数据包进行判断。

大数据华为认证考试(习题卷3)

大数据华为认证考试(习题卷3)第1部分：单项选择题，共51题，每题只有一个正确答案,多选或少选均不得分。

1.[单选题]ElasticSearch 存放所有关键词的地方是()A)字典B)关键词C)词典D)索引答案:C解析:2.[单选题]DWS DN的高可用架构是：（）。

A)主备从架构B)一主多备架构C)两者兼有D)其他答案:A解析:3.[单选题]关于Hive与传统数据仓库的对比，下列描述错误的是:（）。

A)Hive元数据存储独立于数据存储之外，从而解耦合元数据和数据，灵活性高，二传统数据仓库数据应用单一，灵活性低B)Hive基于HDFS存储，理论上存储可以无限扩容，而传统数据仓库存储量有上限C)由于Hive的数据存储在HDFS上，所以可以保证数据的高容错，高可靠D)由于Hive基于大数据平台，所以查询效率比传统数据仓库快答案:D解析:4.[单选题]以下哪种机制使 Flink 能够实现窗口中无序数据的有序处理?（）A)检查点B)窗口C)事件时间D)有状态处理答案:C解析:5.[单选题]下面（）不是属性选择度量。

A)ID3 使用的信息增益B)C4.5 使用的增益率C)CART 使用的基尼指数D)NNM 使用的梯度下降答案:D解析:C)HDFSD)DB答案:C解析:7.[单选题]关于FusionInsight HD Streaming的Supervisor描述正确的是:（）。

A)Supervisor负责资源的分配和任务的调度B)Supervisor负责接受Nimbus分配的任务，启动停止属于自己管理的Worker进程C)Supervisor是运行具体处理逻辑的进程D)Supervisor是在Topology中接收数据然后执行处理的组件答案:B解析:8.[单选题]在有N个节点FusionInsight HD集群中部署HBase时、推荐部署（）个H Master进程，（）个Region Server进程。

鲲鹏应用开发考试(试卷编号241)

鲲鹏应用开发考试(试卷编号241)1.[单选题]以下关于 Kunpeng 920 SAS子系统的说法,哪个是不正确的?A)提供2个X8 SAS 3.0控制器B)支持SAS 3.0.向下兼容SAS 2.0和SAS 1.0C)可以连接 SAS Expander扩展更多磁盘D)可以直接不经过 xpander最大连接8个SAS盘或者SATA盘,但两者不可以混插答案:D解析:2.[单选题]如下那些能力是鲲鹏920芯片独有。

()A)最大核数128B)主频 2.6GhzC)16nm工艺D)内嵌加密模块答案:A解析:3.[单选题]rpmbuild工具的作用是什么?A)构建源码工程B)生成rpm源码文件C)构建rpm包D)发布rpm源码包答案:C解析:4.[单选题]以下哪个不是使用 rpm 工具安装软件?A)自动安装依赖包B)全自动安装C)能够进行数据库的记载D)自定义安装路径答案:A解析:5.[单选题]登录 Porting Advisor 迁移工具时， URL 中的端口是什么A)8085B)8084C)8086D)80826.[单选题]ssh协议默认端号是什么?A)9600B)23C)22D)513答案:C解析:7.[单选题]以下哪种语言的源码文件不能用Porting Advisor迁移工具进行迁移分析?A)CB)汇编C)C++D)Java答案:D解析:8.[单选题]在修改 BenchmarkSL 连接 PostereSL 的配置文件时，关于 runMins 和runTxnsPerTerminal 这两个参数的设置，以下哪项是正确的?A)必须有一个设定为 0B)必须相等C)均为 0D)必须不相等，且均不为 0答案:A解析:9.[单选题]以下哪个命令是 Linux 下用来解压文件的?A)tarB)makeC)psD)wget答案:A解析:10.[单选题]以下哪些属于从 x86 到鲲鹏平台的软件迁移的流程?A)技术分析>功能验证>编译迁移>性能调优B)技术分析>编译迁移>功能验证>性能调优C)性能调优>技术分析>编译迁移>功能验证D)功能验证>技术分析>编译迁移>性能调优答案:B11.[单选题]Kunpeng 920加速引擎不包括下列哪个?A)重删加速引擎B)SSL加速引擎C)压缩加速引擎D)加密算法加速引擎答案:A解析:12.[单选题]在ARMv8架构中,原先ARMv7架构中的Thumb指令被称为什么?A)T64B)A32C)64D)T32答案:D解析:13.[单选题]以下哪种型号的 TaiShan 服务器适合海量的存储环境?A)5280B)2280C)X6000D)2480答案:A解析:14.[单选题]CLI 方式进行代码分析，那些参数是必须选择的（）A)sourceB)compilerC)toolsD)tk答案:A解析:15.[单选题]在默认的配置下，使用Sysbench测试MySQL性能时，下面有哪些不是输出结果的指示值A)压测使用的线程数B)99%的时延C)QPSD)TPS答案:B解析:A)48B)32C)64D)128答案:D解析:17.[单选题]谁是Linux之父?A)RichardMatthewStallmanB)AndrewMortonC)BillGatesD)LimusTorvalds答案:D解析:18.[单选题]以下哪个选项是TaiShan服务器不支持的应用?A)NginxB)DockerC)PostgreSQLD)Oracle答案:D解析:19.[单选题]数据串“hel1o,world/n”开始时在磁盘上,然后被复制到主存,最后从主存上复制到显示设备。

NVIDIA DOCA DNS Filter MLNX-15-060486 _v1.1说明书

Reference ApplicationTable of ContentsChapter 1. Introduction (1)Chapter 2. System Design (2)Chapter 3. Application Architecture (5)Chapter 4. Configuration Flow (6)Chapter 5. Running Application on BlueField (8)Chapter 6. Running Application on Host (10)Chapter 7. References (11)Chapter 1.IntroductionDomain name system (DNS) translates domain names to IP addresses so browsers can load internet resources. Each device connected to the internet has a unique IP address which other machines use to find the device.The DNS process includes several steps:1.Once a user tries to log into a website using a browser, the user's device creates a DNSquery and sends it to a DNS resolver.2.The DNS resolver queries the DNS domain to get an IP address by searching its cache orsending the request to another DNS server.3.Once a match is found, the DNS resolver returns the correct IP matching the DNS domain.4.The user can log into the required website using the correct IP.DNS filter is used to offload DNS requests from the host to the BlueField DPU Arm which allows reducing CPU overhead as Arm allows further DNS processing to be done (e.g., whitelisting, logging, filtering, etc).Chapter 2.System DesignThe DNS filter application is designed to run as a "bump-on-the-wire" on the BlueField-2 DPU instance. The DPU intercepts the traffic coming (ingress traffic) from the wire and either passes it to the Arm or forwards it to the egress port using hairpin. The decision is made by traffic classification.System DesignSystem DesignChapter 3.Application Architecture The DNS filter runs on top of DOCA FLOW to classify DNS requests.1.Ingress packet types are identified using pipes which encapsulate flow rule matchingpatterns and actions.2.Matched flows are identified, and FORWARDING actions can be executed.‣DNS traffic is forwarded to the Arm for further processing‣Non-DNS traffic is forwarded to the egress port using hairpinChapter 4.Configuration Flow1.DPDK initialization.dpdk_init(&argc, &argv, &nb_queues, &nb_ports);2.Stateful flow table (SFT) and port initialization.dpdk_ports_init(nb_queues,nb_ports);‣Mempool allocation‣Rx/Tx and hairpin queue initialization‣DPDK port initialization3.Hairpin binding.enable_hairpin_queues(portid, &peer_ports , 1);‣Binds hairpin queues for the given port ID4.DOCA flow initialization.doca_flow_init(&dns_flow_cfg, &error);5.DOCA flow ports initialization.dns_filter_port_init(&port_cfg, portid);‣Initializes DOCA flow port with the given port configuration for the given port ID.Note: DOCA flow port initialization is done for both ports of the BlueField and after theDPDK ports have been initialized.6.Non-DNS hairpin traffic.build_hairpin_pipes(ports[portid], portid, nb_queues);‣Builds two hairpin pipes, that forward packets to Arm. For a given port, each pipe has one entry for the relevant matching patterns. The first hairpin pipe is for matching UDP non-DNS traffic and the second one is for matching TCP traffic. Note that these pipes are built for both ports of the BlueField.7.Build DNS pipe.build_dns_pipes(ports[portid], portid, nb_queues);‣Builds DNS pipe for a given port. The built pipe has one entry for matching DNS traffic and forwarding it to Arm.8.Processing packets.main_loop(nb_queues, nb_ports);Configuration Flow‣All received packets on Arm, are DNS packets, while non-DNS packets are forwarded to the egress port using hairpin allowing DNS packets to be filtered.Chapter 5.Running Application onBlueField1.Please refer to the DOCA Installation Guide for details on how to install BlueField relatedsoftware.2.To build the applicationa).The DNS filter example is installed as part of the doca-dpi-lib package, the binary islocated under /opt/mellanox/doca/examples/dns_filter/bin/doca_dns_filter.To re-build the DNS filter sample, run:cd /opt/mellanox/doca/examples/dns_filter/srcmeson /tmp/buildninja -C /tmp/builddoca_dns_filter will be created under tmp/build.b).The build process depends on the PKG_CONFIG_PATH environment variable to locatethe DPDK libraries. If the variable was accidently corrupted, and the build fails, run the following command:‣For Ubuntu:export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/opt/mellanox/dpdk/lib/aarch64-linux-gnu/pkgconfig‣For CentOS:export PKG_CONFIG_PATH=$PKG_CONFIG_PATH:/opt/mellanox/dpdk/lib64/pkgconfigc).The DNS filter example is a DPDK application. Therefore, the user is required toprovide DPDK flags and allocate huge pages. Run:echo 1024 > /sys/kernel/mm/hugepages/hugepages-2048kB/nr_hugepages3.To run the application:./doca_dns_filter [dpdk flags] -- -l [log_level]Note: SFs must be enabled according to Scalable Function Setup Guide.For example:/opt/mellanox/doca/examples/dns_filter/bin/doca_dns_filter -aauxiliary:mlx5_core.sf.4 -a auxiliary:mlx5_core.sf.5 -- -l 3Note: The flag -a auxiliary:mlx5_core.sf.4 -a auxiliary:mlx5_core.sf.5 isa must for proper usage of the application. Modifying this flag will result unexpectedbehavior as only two ports are supported. The SF number is arbitrary and configurable.For additional information on available flags for DPDK, use -h before the -- separator. ForRunning Application on BlueField information on available flags for the application, use -h after the -- separator. The -l or –-log_level flag sets the log level for the app (ERR=0, DEBUG=3).Chapter 6.Running Application onHostPlease refer to Running Reference Applications Over Host Guide.Chapter 7.References‣/opt/mellanox/doca/examples/dns_filter/src/dns_filter.cNoticeThis document is provided for information purposes only and shall not be regarded as a warranty of a certain functionality, condition, or quality of a product. NVIDIA Corporation nor any of its direct or indirect subsidiaries and affiliates (collectively: “NVIDIA”) make no representations or warranties, expressed or implied, as to the accuracy or completeness of the information contained in this document and assume no responsibility for any errors contained herein. NVIDIA shall have no liability for the consequences or use of such information or for any infringement of patents or other rights of third parties that may result from its use. This document is not a commitment to develop, release, or deliver any Material (defined below), code, or functionality.NVIDIA reserves the right to make corrections, modifications, enhancements, improvements, and any other changes to this document, at any time without notice. Customer should obtain the latest relevant information before placing orders and should verify that such information is current and complete.NVIDIA products are sold subject to the NVIDIA standard terms and conditions of sale supplied at the time of order acknowledgement, unless otherwise agreed in an individual sales agreement signed by authorized representatives of NVIDIA and customer (“Terms of Sale”). NVIDIA hereby expressly objects to applying any customer general terms and conditions with regards to the purchase of the NVIDIA product referenced in this document. No contractual obligations are formed either directly or indirectly by this document.NVIDIA products are not designed, authorized, or warranted to be suitable for use in medical, military, aircraft, space, or life support equipment, nor in applications where failure or malfunction of the NVIDIA product can reasonably be expected to result in personal injury, death, or property or environmental damage. NVIDIA accepts no liability for inclusion and/or use of NVIDIA products in such equipment or applications and therefore such inclusion and/or use is at customer’s own risk. NVIDIA makes no representation or warranty that products based on this document will be suitable for any specified use. Testing of all parameters of each product is not necessarily performed by NVIDIA. It is customer’s sole responsibility to evaluate and determine the applicability of any information contained in this document, ensure the product is suitable and fit for the application planned by customer, and perform the necessary testing for the application in order to avoid a default of the application or the product. Weaknesses in customer’s product designs may affect the quality and reliability of the NVIDIA product and may result in additional or different conditions and/or requirements beyond those contained in this document. NVIDIA accepts no liability related to any default, damage, costs, or problem which may be based on or attributable to: (i) the use of the NVIDIA product in any manner that is contrary to this document or (ii) customer product designs.No license, either expressed or implied, is granted under any NVIDIA patent right, copyright, or other NVIDIA intellectual property right under this document. Information published by NVIDIA regarding third-party products or services does not constitute a license from NVIDIA to use such products or services or a warranty or endorsement thereof. Use of such information may require a license from a third party under the patents or other intellectual property rights of the third party, or a license from NVIDIA under the patents or other intellectual property rights of NVIDIA.Reproduction of information in this document is permissible only if approved in advance by NVIDIA in writing, reproduced without alteration and in full compliance with all applicable export laws and regulations, and accompanied by all associated conditions, limitations, and notices.THIS DOCUMENT AND ALL NVIDIA DESIGN SPECIFICATIONS, REFERENCE BOARDS, FILES, DRAWINGS, DIAGNOSTICS, LISTS, AND OTHER DOCUMENTS (TOGETHER AND SEPARATELY, “MATERIALS”) ARE BEING PROVIDED “AS IS.” NVIDIA MAKES NO WARRANTIES, EXPRESSED, IMPLIED, STATUTORY, OR OTHERWISE WITH RESPECT TO THE MATERIALS, AND EXPRESSLY DISCLAIMS ALL IMPLIED WARRANTIES OF NONINFRINGEMENT, MERCHANTABILITY, AND FITNESS FOR A PARTICULAR PURPOSE. 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All rights reserved.NVIDIA Corporation | 2788 San Tomas Expressway, Santa Clara, CA 95051。

南开大学22春“物联网工程”《大数据开发技术(二)》期末考试高频考点版(带答案)试卷号：1

南开大学22春“物联网工程”《大数据开发技术（二）》期末考试高频考点版（带答案）一.综合考核(共50题)1.Dstream输出操作中()方法将DStream中的内容按对象序列化并且以SequenceFile的格式保存。

A.printB.saveAsTextFilesC.saveAsObjectFilesD.saveAsHadoopFiles参考答案：D2.GraphX中Edge边对象存有()字段A.srcIdB.dstIdC.attrD.val参考答案：ABC3.如果numPartitions是分区个数，那么Spark每个RDD的分区ID范围是()。

A.[0，numPartitions]B.[0，numPartitions-1]C.[1，numPartitions-1]D.[1，numPartitions]参考答案：B4.MLlib中进行数据标准化的方式有()A.NormalizerB.StandardC.StandardScaleerD.MinMaxScaler5.Spark GraphX中类Graph的joinVertices方法可以()A.收集邻居顶点的顶点Id和顶点属性B.收集邻居顶点的顶点IdC.向指定顶点发送信息并聚合信息D.将顶点信息更新到图中参考答案：D6.Scala列表方法中返回所有元素，除了最后一个的方法是()。

A.dropB.headC.filterD.init参考答案：D7.Mllib中线性会馆算法中的参数reParam表示()A.要运行的迭代次数B.梯度下降的步长C.是否给数据加干扰特征或者偏差特征sso和ridge的正规化参数参考答案：D8.以下哪个方法可以创建RDD()A.parallelizeB.makeRDDC.textFileD.loadFile参考答案：ABCPairRDD中groupBy(func)func返回key，传入的RDD的各个元素根据这个key进行分组。

林子雨大数据技术原理与应用第二章课后题答案

林子雨大数据技术原理与应用第二章课后题答案-标准化文件发布号：（9456-EUATWK-MWUB-WUNN-INNUL-DDQTY-KII大数据第二章课后题答案黎狸1.试述Hadoop和谷歌的MapReduce、GFS等技术之间的关系。

Hadoop是Apache软件基金会旗下的一-个开源分布式计算平台，为用户提供了系统底层细节透明的分布式基础架构。

①Hadoop 的核心是分布式文件系统( Hadoop Ditributed FileSystem,HDFS )和MapReduce。

②HDFS是对谷歌文件系统( Google File System, GFS )的开源实现，是面向普通硬件环境的分布式文件系统，具有较高的读写速度、很好的容错性和可伸缩性，支持大规模数据的分布式存储，其冗余数据存储的方式很好地保证了数据的安全性。

③MapReduce 是针对谷歌MapReduce的开源实现，允许用户在不了解分布式系统底层细节的情况下开发并行应用程序,采用MapReduce 来整合分布式文件系统上的数据，可保证分析和处理数据的高效性。

2.试述Hadoop具有哪些特性。

Hadoop是一个能够对大量数据进行分布式处理的软件框架，并且是以一种可靠、高效、可伸缩的方式进行处理的，它具有以下几个方面的特性。

①高可靠性。

采用冗余数据存储方式，即使一个副本发生故障，其他副本也可以保证正常对外提供服务。

②高效性。

作为并行分布式计算平台，Hadoop采用分布式存储和分布式处理两大核心技术，能够高效地处理PB级数据。

③高可扩展性。

Hadoop的设计目标是可以高效稳定地运行在廉价的计算机集群上，可以扩展到数以千计的计算机节点。

④高容错性。

采用冗余数据存储方式，自动保存数据的多个副本，并且能够自动将失败的任务进行重新分配。

⑤成本低。

Hadoop采用廉价的计算机集群，成本比较低，普通用户也很容易用自己的PC搭建Hadoop运行环境。

Blast常用参数简析

Formatdb命令行参数formatdb - 得到formatdb 所有的参数显示（见附录二）和介绍，它可以根据我们的想法把源数据库格式化.主要参数的说明:-i 输入需要格式化的源数据库名称 Optional-p 文件类型，是核苷酸序列数据库，还是蛋白质序列数据库T – protein F - nucleotide [T/F] Optionaldefault = T-a 输入数据库的格式是ASN.1（否则是FASTA）T - True, F - False. [T/F] Optionaldefault = F-o 解析选项T - True: 解析序列标识并且建立目录F - False: 与上相反[T/F] Optional default = F命令示例:formatdb -i ecoli.nt -p F -o T运行此命令就会在当前目录下产生用于BLAST搜索的7个文件，一旦如上的formatdb命令执行完毕，就不再需要ecoli.nt，可以移除。

此时，blastall可以直接使用。

Blastall常用参数简析BLAST (Basic Local Alignment Search Tool) 基本局部比对搜索工具，是一套在蛋白质数据库或DNA数据库中进行相似性比较的分析工具，它是基于Altschul等人在J.Mol.Biol上发表的方法(J.Mol.Biol.215:403-410(1990)),在序列数据库中对查询序列进行同源性比对工作。

BLAST程序能迅速与公开数据库进行相似性序列比较，利用比较结果中的得分对序列相似性进行说明。

BLAST可以对一条或多条序列(可以是任何形式的序列)在一个或多个核酸或蛋白序列库中进行比对，并且从最初的BLAST发展到现在NCBI提供的BLAST2.0,已将有缺口的比对序列也考虑在内了。

BLAST可处理任何数量的序列,包括蛋白序列和核酸序列;也可选择多个数据库但数据库必须是同一类型的,即要么都是蛋白数据库要么都是核酸数据库。

Fortinet高级网络安全产品说明说明书

The ultimate combination of proactive mitigation, advanced threat visibility and comprehensive reporting.§Secure virtual runtime environment exposes unknown threats §Unique multi-layer prefilters aid fast and effective threat detection §Rich reporting provides full threat lifecycle visibility§Inspection of many protocols in one appliance simplifies deployment and reduces cost §Integration and automation with Fortinet threat prevention products enhances rather than duplicates security infrastructure §Independent testing and certification validates effectivenessengine, queries to cloud-based threat databases and OS-independent simulation with acode emulator, followed by execution in the full virtual runtime environment. Once a malicious code is detected, granular ratings along with key threat intelligence is available, a signature is dynamically created for distribution to integrated products and full threat information is optionally shared with FortiGuard Labs for the update of global threat databases.Actionable InsightAll classifications — malicious and high/medium/low risk — are presented within an intuitive dashboard. Full threat information from the virtual execution — including system activity, exploit efforts, web traffic, subsequent downloads, communication attempts and more — is available in rich logs and reports.DATA SHEETFortiSandbox ™Multi-layer proactive threat mitigationFortiGuard Security ServicesFortiCare Worldwide 24x7 SupportFortinet Security Fabric/sf2 DATA SHEET: FortiSandbox ™ADVANCED THREAT PROTECTION FRAMEWORKPrevent AttacksFortinet next generation firewalls, secure email gateways, web application firewalls, endpoint security and similar solutions use security such as antivirus, web filtering, IPS, and other traditional security techniques to quickly and efficiently prevent known threats from impacting an organization.Detect and Analyze ThreatsFortiSandbox and other advanced detection techniques step in to detect “Zero-day” threats and sophisticated attacks, delivering risk ratings and attack details necessary for remediation.Mitigate Impact and Improve ProtectionIn a Fortinet solution, detection findings can be used to trigger prevention actions to ensure the safety of resources and data until remediation is in place. Finally, the entire security ecosystem updates to mitigate any impact from future attacks through the strong, integrated threat intelligence research and services ofFortiGuard Labs.FORTINET SECURITY FABRICThe most effective defense against advanced targeted attacks is founded on a cohesive and extensible protection framework. The Fortinet framework uses security intelligence across an integrated solution of traditional and advanced security tools for network, application and endpoint security, and threat detection to deliver actionable, continuously improving protection.Fortinet integrates the intelligence of FortiGuard Labs into FortiGate next generation firewalls, FortiMail secure email gateways, FortClient endpoint security, FortiSandbox advanced threat detection, and other security products to continually optimize and improve the level of security delivered to organizations with a Fortinet solution.Fortinet is the only company with security solutions for network, endpoint, application, data center, cloud, and access designed to work together as an integrated and collaborative security fabric. Simply deploying security end to end is not enough. These solutions must work together to form a cooperative fabric that can scale to cover the entire network, with different security sensors and toolsthat are aware of each other and operate as a single entity, even when sourced from multiple vendors. Further components must collect, coordinate, and respond to any potential threat in real-time with actionable intelligence. This is where FortiSandbox and the broader Advanced Threat Protection solution set fits.3DATA SHEET: FortiSandbox ™DEPLOYMENT OPTIONSStandaloneThis deployment mode relies on inputs from spanned switch ports or network taps. It may also include administrators’ on-demand file uploads using the GUI. It is the most suitable infrastructure for adding protection capabilities to existing threat protection systems from various vendors.IntegratedVarious Fortinet products, namely FortiGate, FortiMail, FortiWeb and FortiClient can intercept and submit suspicious content to FortiSandbox when they are configured to interact with FortiSandbox. The integration will also provide timely remediation and reporting capabilities to those devices.* Not applicable to FortIWebDistributedThis deployment is attractive for organizations that have distributed environments, where FortiGates are deployed in the branch offices and submit suspicious files to a centrally-located FortiSandbox. This setup yields the benefits of lowest TCO and protects against threats in remote locations.File and URL SubmissionFortiSandboxOn-Demand InputEasy DeploymentFortiSandbox supports inspection of many protocols in one unified solution, thus simplifies network infrastructure and operations. Further, it integrates with FortiGate as a new capability within your existing security framework.The FortiSandbox is the most flexible threat analysis appliance in the market as it offers various deployment options for customers’ unique configurations and requirements. Organizations can also have all three input options at the same time.4 DATA SHEET: FortiSandbox ™FEATURES SUMMARYFEATURESAV Engine§Applies top-rated (95%+ Reactive and Proactive) AV Scanning. Serves as an efficient pre-filter.Cloud Query§Real-time check of latest malware information §Access to shared information for instant malware detectionCode Emulation§Quickly simulates intended activity §OS independent and immune to evasion/obfuscationFull Virtual Sandbox§Secure run-time environment for behavioral analysis/rating§Exposes full threat lifecycle informationCall Back Detection§Identifies the ultimate aim, call back andexfiltrationMulti-tiered file processing optimizes resource usage thatimproves security, capacity and performanceFile Submission input: FortiGate, FortiClient, FortiMail, FortiWeb File Status Feedback and Report: FortiGate, FortiClient, FortiMail, FortiWeb Dynamic Threat DB update: FortiGate, FortiClient, FortiMail – Periodically push dynamic DB to registered entities. – File checksum and malicious URL DB Update Database proxy: FortiManager Remote Logging: FortiAnalyzer, syslog serverWeb-based API with which users can upload samples to scan indirectly Bit9 end point software integrationAdvanced Threat ProtectionVirtual OS Sandbox: – Concurrent instances– OS type supported: Windows XP , Windows 7, Windows 8.1, Windows 10 and Android – Anti-evasion techniques: sleep calls, process and registry queries– Callback Detection: malicious URL visit, Botnet C&C communication and attacker traffic from activated malware – Download Capture packets, Original File, Tracer log and ScreenshotFile type support: .7z, .ace, .apk, .arj, .bat, .bz2, .cab, .cmd, .dll, .doc, .docm, .docx, .dot, .dotm, .dotx, .exe, .gz, .htm, html, .htmnojs, .jar, .js, .kgb, .lnk, .lzh, .msi, .pdf, .pot, .potm, .potx, .ppam, .pps, .ppsm, .ppsx, .ppt, .pptm, .pptx, .ps1, .rar, .rtf, .sldm, .sldx, .swf, .tar, .tgz, .upx, url, .vbs, WEBLink, .wsf, .xlam, .xls, .xlsb, .xlsm, .xlsx, .xlt, .xltm, .xltx, .xz, .z, .zipProtocols/applications supported:– Sniffer mode: HTTP , FTP , POP3, IMAP , SMTP , SMB – I ntegrated mode with FortiGate: HTTP , SMTP , POP3, IMAP , MAPI, FTP , IM and their equivalent SSL encrypted versions– Integrated mode with FortiMail: SMTP , POP3, IMAP – Integrated mode with FortiWeb: HTTP – Integrated mode with ICAP Client: HTTP Customize VMs with support file types support Isolate VM image traffic from system trafficNetwork threat detection in Sniffer Mode: Identify Botnet activities and network attacks, malicious URL visit Scan SMB/NFS network share and quarantine suspicious files. Scan can be scheduled Scan embedded URLs inside document files Integrate option for third partyYara rulesOption to auto-submit suspicious files to cloud service for manual analysis and signature creation Option to forward files to a network share for further third-party scanning Files checksum whitelist and blacklist optionURLs submission for scan and query from emails and filesMonitoring and ReportReal-Time Monitoring Widgets (viewable by source and time period options): Scanning result statistics, scanning activities (over time), top targeted hosts, top malware, top infectious urls, top callback domains Drilldown Event Viewer: Dynamic table with content of actions, malware name, rating, type, source, destination, detection time and download path Logging — GUI, download RAW log fileReport generation for malicious files: Detailed reports on file characteristics and behaviors – file modification, process behaviors, registry behaviors, network behaviors, vm snapshot, behavior chronology chart Further Analysis: Downloadable files — Sample file, Sandbox tracer logs, PCAP capture and Indicators in STIX format5Dashboard widgets — real-time threat statusFile Analysis ToolsReports with captured packets, original file, tracer log and screenshot provide rich threat intelligence and actionable insight after files are examined. This is to speed up remediation and updated protection.RemediationFortinet’s ability to uniquely integrate various products with FortiSandbox offers automatic protection with incredibly simple setup. Once a malicious code is determined, the analyzer will develop and forward the dynamically generated signature to all registered devices and clients. These devices then examine subsequent files against the latest DB.FortiGuard LabsFile submission for analysis, results returned12a 3a Optionally share analysis with FortiGuard3b Quarantine devices, block traf fi c by fi rewall2b fi le or device by2c 2d QueryMitigate4Update6 AV Scanning (Files/Hour)Hardware dependent–Number of VMs4 to 54 (Upgrade via appropriate licenses)–* Based on the assumption that 1 blade will be used as master in HA-cluster mode. ** By adding 3 more SAM-3500D nodes to the same chassis.*** 8 Windows VM licenses included with hardware, remaining 48 sold as an upgrade license.FortiSandbox 1000D FortiSandbox 3000DFortiSandbox 3500DFortiSandbox 3000EGLOBAL HEADQUARTERS Fortinet Inc.899 Kifer RoadSunnyvale, CA 94086United StatesTel: +/salesEMEA SALES OFFICE 905 rue Albert Einstein Valbonne 06560Alpes-Maritimes, France Tel: +33.4.8987.0500APAC SALES OFFICE 300 Beach Road 20-01The Concourse Singapore 199555Tel: +65.6395.2788LATIN AMERICA SALES OFFICE Sawgrass Lakes Center13450 W. Sunrise Blvd., Suite 430 Sunrise, FL 33323United StatesTel: +1.954.368.9990Copyright© 2016 Fortinet, Inc. All rights reserved. Fortinet®, FortiGate®, FortiCare® and FortiGuard®, and certain other marks are registered trademarks of Fortinet, Inc., and other Fortinet names herein may also be registered and/or common law trademarks of Fortinet. All other product or company names may be trademarks of their respective owners. Performance and other metrics contained herein were attained in internal lab tests under ideal conditions, and actual performance and other results may vary and may be signiﬁcantly less effective than the metrics stated herein. Network variables, different network environments and other conditions may negatively affect performance results and other metrics stated herein. Nothing herein represents any binding commitment by Fortinet, and Fortinet disclaims all warranties, whether express or implied, except to the extent Fortinet enters a binding written contract, signed by Fortinet’s General Counsel, with a purchaser that expressly warrants that the identiﬁed product will perform according to certain expressly-identiﬁed performance metrics and, in such event, only the speciﬁc performance metrics expressly identiﬁed in such binding written contract shall be binding on Fortinet and any such commitment shall be limited by the disclaimers in this paragraph and other limitations in the written contract. For absolute clarity, any such warranty will be limited to performance in the same ideal conditions as in Fortinet’s internal lab tests, and in no event will Fortinet be responsible for events or issues that are outside of its reasonable control. Notwithstanding anything to the contrary, Fortinet disclaims in full any covenants, representations, and guarantees pursuant hereto, whether express or implied. Fortinet reserves the right to change, modify, transfer, or otherwise revise this publication without notice, and the most current version of the publication shall be applicable.FST -PROD-DS-FSAFSA-DAT -R18-201609DATA SHEET: FortiSandbox ™1 GE SFP SX Transceiver Module FG-TRAN-SX 1 GE SFP SX transceiver module for all systems with SFP and SFP/SFP+ slots.1 GE SFP LX Transceiver ModuleFG-TRAN-LX 1 GE SFP LX transceiver module for all systems with SFP and SFP/SFP+ slots.10 GE SFP+ Transceiver Module, Short Range FG-TRAN-SFP+SR 10 GE SFP+ transceiver module, short range for all systems with SFP+ and SFP/SFP+ slots.10 GE SFP+ Transceiver Module, Long RangeFG-TRAN-SFP+LR10 GE SFP+ transceiver module, long range for all systems with SFP+ and SFP/SFP+ slots.INTEGRATION MATRIXFSA Appliance and VMFile Submission *FortiOS V5.0.4+FortiClient for Windows OS V5.4+FortiMail OS V5.1+FortiWeb OS V5.4+File Status Feedback *FortiOS V5.0.4+FortiClient for Windows OS V5.4+FortiMail OS V5.1+FortiWeb OS V5.4+File Detailed Report *FortiOS V5.4+FortiClient for Windows OS V5.4+FortiMail OS V5.1+–Dynamic Threat DB Update*FortiOS V5.4+FortiClient for Windows OS V5.4+FortiMail OS V5.3+FortiWeb OS V5.4+FortiSandbox CloudFile Submission *FortiOS V5.2.3+–FortiMail OS V5.3+FortiWeb OS 5.5.3+File Status Feedback *FortiOS V5.2.3+–FortiMail OS V5.3+FortiWeb OS 5.5.3+File Detailed Report *FortiOS V5.2.3+–––Dynamic Threat DB Update*FortiOS V5.4+–FortiMail OS V5.3+FortiWeb OS 5.5.3+*some models may require CLI configurationORDER INFORMATION。

互联网大厂面试题目答案

阿里篇1.1.1 如何实现一个高效的单向链表逆序输出？1.1.2 已知sqrt(2)约等于1.414，要求不用数学库，求sqrt(2)精确到小数点后10位1.1.3 给定一个二叉搜索树(BST)，找到树中第K 小的节点1.1.4 LRU缓存机制1.1.5 关于epoll和select的区别，以下哪些说法是正确的1.1.6 从innodb的索引结构分析，为什么索引的key 长度不能太长1.1.7 MySQL的数据如何恢复到任意时间点？1.1.8 NFS 和SMB 是最常见的两种NAS（Network Attached Storage）协议，当把一个文件系统同时通过NFS 和SMB 协议共享给多个主机访问时，以下哪些说法是错误的1.1.9 输入ping IP 后敲回车，发包前会发生什么？1.2.0 请解释下为什么鹿晗发布恋情的时候，微博系统会崩溃，如何解决？1.2.1 现有一批邮件需要发送给订阅顾客，且有一个集群（集群的节点数不定，会动态扩容缩容）来负责具体的邮件发送任务，如何让系统尽快地完成发送？1.2.2 有一批气象观测站，现需要获取这些站点的观测数据，并存储到Hive 中。

但是气象局只提供了api 查询，每次只能查询单个观测点。

那么如果能够方便快速地获取到所有的观测点的数据？1.2.3 如何实现两金额数据相加（最多小数点两位）1.2.4 关于并行计算的一些基础开放问题1.2.5 请计算XILINX公司VU9P芯片的算力相当于多少TOPS，给出计算过程与公式1.2.6 一颗现代处理器，每秒大概可以执行多少条简单的MOV指令，有哪些主要的影响因素1.2.7 请分析MaxCompute 产品与分布式技术的关系、当前大数据计算平台类产品的市场现状和发展趋势1.2.8 对大数据平台中的元数据管理是怎么理解的，元数据收集管理体系是怎么样的，会对大数据应用有什么样的影响1.2.9 你理解常见如阿里，和友商大数据平台的技术体系差异以及发展趋势和技术瓶颈，在存储和计算两个方面进行概述1.3.0 在云计算大数据处理场景中，每天运行着成千上万的任务，每个任务都要进行IO 读写。

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BloomFilter-basedXMLPacketsFilteringforMillionsofPathQueriesXueqingGong,WeiningQian,YingYan,andAoyingZhouDepartmentofComputerScienceandEngineeringFudanUniversity,Shanghai,P.R.China{gongxq,wnqian,yingyan,ayzhou}@fudan.edu.cn

AbstractTheﬁlteringofXMLdataisthebasisofmanycomplexapplications.Lotsofalgorithmshavebeenproposedtosolvethisproblem[2,3,5,6,7,8,9,11,12,13,18].Oneimportantchallengeisthatthenumberofpathqueriesishuge.Itisnecessarytotakeanefﬁcientdatastructurerep-resentingpathqueries.Anotherchallengeisthatthesepathqueriesusuallyvarywithtime.Themaintenanceofpathqueriesdeterminestheﬂexibilityandcapacityofaﬁlteringsystem.Inthispaper,weintroduceanovelapproximatemethodforXMLdataﬁltering,whichusesBloomﬁltersrepresent-ingpathqueries.Inthismethod,millionsofpathqueriescanbestoredefﬁciently.Atthesametime,itiseasytodealwiththechangeofthesepathqueries.Toimprovetheﬁlter-ingperformance,weintroduceanewdatastructure,PreﬁxFilters,todecreasethenumberofcandidatepaths.Exper-imentsshowthatourBloomﬁlter-basedmethodtakeslesstimetobuildroutingtablethanautomaton-basedmethod.AndourmethodhasagoodperformancewithacceptablefalsepositivewhenﬁlteringXMLpacketsofrelativelysmalldepthwithmillionsofpathqueries.

1.IntroductionXMLisquicklygainingdominanceasaformatforex-changingandstoringsemi-structureddata.Plentyofinfor-mationisrepresentedinXMLformatandisdeliveredtoendusersorclients.Forexample,inapublish/subscribesystem,userssubscribenewsorproductioninformationtotheirser-viceproviders.Serviceprovidersshouldﬁlteralltheirin-formationanddelivertouserswhattheywant.Suchappli-cationsincludestockandsportstickers,trafﬁcinformationsystem,electronicpersonalizednewspaper,andentertain-mentdelivery.Insuchenvironments,newinformationisproducedcontinuallyandthetotalamountofinformationishuge.MostofsuchinformationisrepresentedinXMLformatandisprocessedasastream.Furthermore,users’interestcouldvarywithtime.Theseapplicationsmustdealwiththechangeoftheirusers’interestefﬁciently.There-fore,theprocessingperformanceandqueriesmaintenancearebothcriticalfortheseapplications.Recently,lotsofworkshavebeenproposedforXMLﬁl-teringandstreamprocessing[2,3,5,6,7,8,9,11,12,13,18].AlltheseworkstakeastreamofXMLdocumentsasinput,andcomputepathqueriesagainstthestreamtoiden-tifythematches.Ingeneral,thedocumentsinthestreamaresmallpackets,calledasXMLPackets.User’sinterestsarerepresentedasXMLpathqueriesintheseworks.Inthispaper,wefocusonthescenarioofXMLdatadissemination,wheremanyXMLpathqueriesarepreprocessedtobuildaroutingtable,andincomingXMLpacketsareevaluatedontheroutingtablefordissemination.Therehavebeentwotypesofworksofsolvingthisproblem,automaton-basedmethods[2,8,12,11,9]andindex-basedmethod[5].TheformertransformsXMLpathqueriesintoanautomaton,suchasNFA,DFAorPushdownMachine.Then,incom-ingXMLpacketsarenavigatedthroughtheautomatontoidentifythematchedqueriesandrelevantusers.ThelattercombinesXMLpathqueriesintoapreﬁxtreeandbuildsanelementpositionindexfortheincomingXMLpacket.Then,thepreﬁxtreeiscomputedbasedontheindexforthematchedqueries.Incasetheautomatonortheindexhasbeenconstructed,bothofthemcanprocessincomingXMLpacketsefﬁciently.However,inthescenarioswherethenumberofXMLpathqueriesishugeorthesetofXMLpathquerieschanges,theefﬁciencyandthemaintenanceofroutingtablewouldbethebottleneckofsystems.ThispaperproposesanoveltechnologyforXMLpack-etsﬁltering.WetakeanXMLpathqueryasaquerystring,andallquerystringsofoneuseraremappedintoaBloomﬁlterbyhashfunctions.TheroutingtableiscomprisedofmanyBloomﬁlters.ForeachincomingXMLpacket,itisparsedtogenerateasetofcandidatepaths,whileeachcan-didatepathismappedtoabit-vectorbythesamehashfunc-tionstocomparewiththeroutingtable.Ifacandidatepathisdeterminedexistinginauser’sBloomﬁlter,therelatedXMLpacketfragmentisroutedtotheuser.Themaincon-tributionsofourworkarethefollowing:•WepresentanoveltechnologyofﬁlteringXMLpack-ets,i.e.Bloomﬁlter-basedﬁltering.ItcanﬁlterXMLpacketsefﬁcientlywithrelativelylowfalsepositive.Inthescenariothatthenumberofpathqueriesishuge,ourtechnologyhasobviouslyadvantageinefﬁciencyandroutingtablemaintenance.•Toimprovetheperformanceofﬁltering,weintroduceanewdatastructure,i.e.PreﬁxFilters.Itcanimprovetheﬁlteringperformancegreatlybydecreasingthenumberofcandidatepaths.•WepresentanempiricalstudyofBloomﬁlter-basedandautomaton-basedﬁltering.ExperimentsshowthattheformerhasbetterperformancewhenthenumberofpathqueriesishugeandthedepthofXMLpacketsisrelativelysmall.1.1PaperOrganizationTherestofthepaperisstructuredasfollows.Section2isdedicatedtosomebackgroundknowledgeandtheproblemstatement.InSection3wepresentourbasicapproachofﬁlteringXMLpacketsusingBloomﬁlters.Section4in-troducespreﬁxﬁltersandthemaintenanceofroutingta-ble.Section5reportsourexperimentalresults.Section6presentsrelatedresearchworksandSection7concludesthepaper.2.BackgroundInthissection,weintroduceXMLpacketsandsimplepathqueriesthatweprocess.AnoverviewofBloomﬁlterisalsopresentedfollowedbyourproblemstatement.2.1.XMLPacketsandPathQueriesAnXMLdocumentcanberepresentedasarootedla-belledtree,whereeachnodecorrespondstoanelementoravalue.ThereisarootnodeforeachXMLdocument.Foreachelement,thereisauniquepathfromtherootnodetoitwhichiscalledasitsNodePath.Thedepthofanodepathequalstothenumberofnodesinit.ThemaximaldepthofallnodepathsisthedepthoftheXMLdocument.Ingeneral,thedepthsofmostXMLdocumentstransmittedinnetworksarenotlarge.Thispaperfocusesonthedis-seminationofXMLpackets,whicharesmalldepthXMLdocuments.SeveralquerylanguageshavebeenproposedforXMLdataprocessing,suchasXQuery,XSLTandXPath.Thebasisofthesequerylanguagesispathexpressions.Inthispaper,weconsiderthesimplepathquerywhichisdescribedindeﬁnition1.