`

Spark API编程动手实战-02-以集群模式进行Spark API实战textFile、cache、count

阅读更多

操作HDFS:先要保证HDFS启动了:

启动spark集群:

以spark-shell运行在spark集群上:

 

查看下之前上传到HDFS上的”LICENSE.txt“文件:

用spark读取这个文件:

使用count统计该文件的行数:

 我们可以看到count 耗时为0.239708s

对该RDD进行cache操作并执行count使得缓存生效:

执行count结果为:

此时耗时为0.21132s

再执行count操作:

此时耗时为0.029580s,这时因为我们自己基于cache后的数据进行操作的。

接着我们对上面的rdd进行wordcount操作:

通过saveAsTextFile把数据存到HDFS中:

我们通过web控制台查看下运行结果:

我们通过命令行看下part-00000和part-00001内容:

[spark@S1PA222 ~]$ hadoop fs -cat /data/resultLicenseWordCount/part-00000
15/01/22 13:51:32 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
(under,10)
(Unless,3)
(Contributions),1)
(offer,1)
(agree,1)
(BUSINESS,2)
(NON-INFRINGEMENT,,1)
(its,4)
(materials,2)
(event,1)
(intentionally,2)
(Grant,2)
(writing,1)
(include,3)
(responsibility,,1)
(have,2)
(MERCHANTABILITY,,1)
(Contribution,3)
(Massachusetts,1)
(express,2)
("Your"),1)
((i),1)
(However,,1)
(been,2)
(files;,1)
(This,1)
(stating,1)
(2-Clause,1)
(conditions.,1)
(non-exclusive,,2)
(appropriateness,1)
(marked,1)
(risks,1)
(any,28)
(IS",4)
(implementation,1)
(filed.,1)
(Sections,1)
(fee,1)
(losses),,1)
(out,1)
(contract,2)
(DISTRIBUTION,1)
(4.,1)
(file,6)
(documentation,,2)
(wherever,1)
(unless,1)
(below).,1)
(names,,1)
(verbal,,1)
(ANY,10)
(version,1)
(file.,2)
(are,10)
(no-charge,,2)
(2.,1)
(from,,1)
(reproduction,,3)
(2011-2014,,1)
(assume,1)
(licenses,1)
(DATA,,2)
(IS,2)
(recommend,1)
(prominent,1)
(revisions,,1)
("[]",1)
(FITNESS,3)
(otherwise,,3)
(distribution,,1)
(necessarily,1)
(Apache,5)
(grant,1)
(CONTRIBUTORS,4)
(as,15)
(irrevocable,2)
(inclusion,2)
(purpose,2)
(products,1)
(ARE,2)
(merely,1)
(File,1)
(Definitions.,1)
(form,10)
(IMPLIED,4)
(Warranty,1)
(Patent,1)
(incurred,1)
(8.,1)
(repository,1)
(contributors,1)
("printed,1)
(sell,,2)
(:,3)
(malfunction,,1)
(Version,2)
(origin,1)
(alongside,1)
(CRC,1)
(implied.,1)
(contract,,1)
(representatives,,1)
(warranty,1)
(offer,,1)
(org.apache.hadoop.util.bloom.*,1)
(KIND,,2)
(is,10)
(conspicuously,1)
(found,1)
(charge,1)
(make,,1)
(file,,1)
(associated,1)
(even,1)
(same,1)
((Don't,1)
(outstanding,1)
(link,1)
([name,1)
(Trademarks.,1)
(notice,2)
(endorse,1)
(shall,15)
(contact,1)
(Redistributions,4)
(using,1)
(class,1)
(name),1)
(behalf,5)
(form.,1)
(We,1)
(INTERRUPTION),2)
(responsible,1)
(annotations,,1)
(THIS,4)
(subject,1)
(acting,1)
(permitted,2)
(OUT,2)
(BASIS,,2)
(has,2)
(Accepting,1)
(defend,,1)
(University,1)
([yyyy],1)
((http://www.one-lab.org),1)
(EVENT,2)
(granting,1)
(portions,1)
(implied,,1)
(NOTICE,5)
(infringed,1)
(limitation,,1)
(names,2)
(electronic,,1)
(PURPOSE,2)
(licensable,1)
(section),1)
(conditions,14)
(EVEN,2)
(acts),1)
(law,3)
(licenses.,1)
(compression,1)
(readable,1)
(solely,1)
(configuration,1)
(information.,1)
(litigation,2)
(represent,,1)
(warranty,,1)
(shares,,1)
(supersede,1)
(governed,1)
(marks,,1)
(http://code.google.com/p/lz4/,1)
(modification,,2)
(fifty,1)
(sent,1)
(places:,1)
(means,2)
(identifying,1)
(this,22)
(Works",1)
(Louvain,1)
(prior,1)
(slicing-by-8,1)
(PROCUREMENT,2)
(changed,1)
(describing,1)
(only,4)
(contributory,1)
(normally,1)
(indirect,,2)
(WITHOUT,2)
(Works,12)
(documentation,3)
(agreement,1)
(otherwise,3)
("AS,4)
(damages,,1)
(patent,,1)
(APACHE,1)
(without,6)
("NOTICE",1)
(Limitation,1)
(SUBSTITUTE,2)
(Contribution(s),3)
(Subject,2)
(Submission,1)
(UCL,1)
(TITLE,,1)
(trademarks,,1)
((iii),1)
(2.0,1)
(Fast,1)
(exercise,1)
(accepting,2)
(example,1)
(distribution.,2)
(interfaces,1)
(conditions:,1)
(act,1)
(incorporated,2)
(provides,2)
(limited,4)
(LZ4,3)
(2008,2009,2010,1)
(can,2)
(contents,1)
(PURPOSE.,1)
(recipients,1)
("Contribution",1)
(failure,1)
(communication,3)
(commercial,1)
(works,1)
(language,1)
(permissions,3)
(WARRANTIES,4)
(media,1)
(reserved.,2)
(Works,,2)
(How,1)
(WARRANTIES,,2)
(controlled,1)
(Warranty.,1)
(2.0,,1)
((http://www.opensource.org/licenses/bsd-license.php),1)
(own,4)
(submit,1)
(SHALL,2)
(reasonable,1)
(reason,1)
(agreed,3)
(systems,1)
(patent,5)
(form,,4)
(Technology.,1)
(advised,1)
(systems,,1)
(classes:,1)
(HOWEVER,2)
(distribution,3)
(DAMAGES,2)
((c),2)
(src/main/native/src/org/apache/hadoop/util:,1)
(PROFITS;,2)
(perpetual,,2)
(applies,1)
(apply,2)
(subcomponents,2)
(modify,2)
(owner],1)
(one,1)
(modifying,1)
(counterclaim,1)
(January,1)
(discussing,1)
(CONTRACT,,2)
(with,16)
((C),1)
(infringement,,1)
(2004,1)
(lawsuit),1)
(specific,2)
(LZ,1)
(warranties,1)
(reproducing,1)
(promote,1)
(beneficial,1)
(ADVISED,2)
((a),1)
(other,9)
(date,1)
(met:,2)
(publicly,2)
(from,4)
(LIMITED,4)
(display,,1)
(MERCHANTABILITY,2)
(damages,3)
(SUBCOMPONENTS:,1)
(negligence),,1)
(remain,1)
(CONDITIONS,4)
(their,2)
(electronic,1)
(identification,1)
(determining,1)
(consistent,1)
(display,1)
(writing,,3)
(trade,1)
(third-party,2)
(,1299)
(description,1)
(REPRODUCTION,,1)
(attached,1)
(list,4)
(*,34)
(INDIRECT,,2)
(designated,1)
(Contribution.",1)
(complies,1)
(addendum,1)
(damages.,1)
(Yann,1)
(EXPRESS,2)
(License;,1)
(6.,1)
(GOODS,2)
(subsequently,1)
(included,2)
(replaced,1)
(notice,,5)
[spark@S1PA222 ~]$   hadoop fs -cat /data/resultLicenseWordCount/part-00001

15/01/22 13:52:29 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
(For,6)
(reproduce,,1)
("Contributor",1)
((or,3)
(nothing,1)
(work.,1)
(content,1)
(HOLDERS,2)
(add,2)
(through,1)
(All,2)
(perform,,1)
(result,1)
(goodwill,,1)
(herein,1)
(direct,,1)
(used,1)
(To,1)
(harmless,1)
(9.,1)
(these,1)
(control,,1)
(INCIDENTAL,,2)
(indicated,1)
(part,4)
(alone,1)
(different,1)
(forms,,2)
(purposes,4)
(https://groups.google.com/forum/#!forum/lz4c,1)
(be,7)
(/**,2)
(carry,1)
(separable,1)
(including,5)
(contained,1)
(combination,1)
(calculation,1)
(license,7)
(FOR,6)
(thereof,,2)
(ARISING,2)
(constitutes,1)
(but,5)
(types.,1)
(stated,2)
(archives.,1)
(obligations,,1)
(5.,1)
(Works;,3)
(nor,1)
("Legal,1)
(Work,20)
(whole,,2)
(Copyright,5)
(at,3)
(copyright,,1)
(Redistribution,2)
(object,1)
(copy,3)
(indemnify,,1)
(asserted,1)
(HADOOP,1)
(attach,1)
("control",1)
(support,,1)
("Object",1)
(give,1)
(THEORY,2)
(may,10)
(except,2)
("Work",1)
(sublicense,,1)
(IF,2)
(granted,2)
(project,2)
(authorized,2)
(SPECIAL,,2)
(BY,2)
(retain,2)
(or,65)
(transfer,1)
(fields,1)
(Licensor,,1)
((b),1)
((ii),1)
(2005,,1)
(of,75)
(does,1)
(transformation,1)
((INCLUDING,2)
(DIRECT,,2)
(management,1)
(modified,1)
(Licensed,1)
(percent,1)
(Header,1)
(original,2)
(Contributor,,1)
(native,1)
((INCLUDING,,2)
(PARTICULAR,3)
(limitations,1)
(THE,10)
(INCLUDING,,2)
(power,,1)
(CAUSED,2)
(de,1)
(appropriate,1)
(against,,1)
(TORT,2)
("Source",1)
(each,4)
(1.,1)
(following,10)
(Liability.,2)
(acceptance,1)
("You",1)
(sole,1)
(from),1)
(See,1)
(tracking,1)
(for,19)
(cause,2)
(alleging,1)
(obtain,1)
(reproduce,3)
(source,,1)
(control,2)
(EXEMPLARY,,2)
(TERMS,2)
(terms,8)
(syntax,1)
(SERVICES;,2)
(made,,1)
(BUT,4)
(compiled,1)
(issue,1)
("submitted",1)
(OneLab,1)
(algorithm,1)
(was,1)
(While,1)
(entity,,1)
(do,3)
(PROVIDED,2)
(no,2)
(License,10)
(entity,3)
(Contributions.,2)
(mean,10)
(individual,3)
(Institute,1)
(computer,1)
(notices,9)
(Neither,1)
(Licensor,8)
(STRICT,2)
(made,1)
(authorship,,2)
(bind,1)
((the,1)
(indemnity,,1)
(distribute,3)
(You,24)
(grants,2)
(brackets,1)
(meet,1)
(for,,1)
(service,1)
(in,31)
(trademark,,1)
(boilerplate,1)
(WAY,2)
(LOSS,2)
(distributed,3)
(LIABILITY,,4)
(submitted,2)
(public,1)
(OF,19)
(managed,1)
(derived,2)
(Source,8)
(use,,4)
(name,2)
(definition,,2)
(that,25)
(src/main/native/src/org/apache/hadoop/io/compress/lz4/{lz4.h,lz4.c,lz4hc.h,lz4hc.c},,1)
(customary,1)
(BSD,1)
(thereof,1)
(claims,2)
(CONSEQUENTIAL,2)
(translation,1)
(format.,1)
(construed,1)
(DAMAGE.,2)
(applicable,3)
(binary,4)
(regarding,1)
(European,1)
(excluding,3)
(END,1)
((d),1)
(choose,1)
(NO,2)
(BE,2)
(direct,2)
(retain,,1)
(modifications,,3)
(forum,1)
(owner,4)
(USE,2)
(informational,1)
(The,3)
(legal,1)
((50%),1)
(document.,1)
(received,1)
(such,17)
(institute,1)
(distribute,,2)
(WHETHER,2)
(page",1)
((except,1)
(loss,1)
(common,1)
(additions,1)
(BSD-style,1)
(Appendix,1)
(Use,1)
(disclaimer,2)
(resulting,1)
(ON,2)
(hereby,2)
(License.,11)
(software,3)
(whom,1)
(along,1)
(lists,,1)
(required,4)
(OR,18)
(ownership,2)
(SOFTWARE,2)
(the,122)
(includes,1)
(obligations,1)
(import,,1)
(not,11)
(either,2)
(terminate,1)
(if,4)
(stoppage,,1)
(provided,9)
(submitted.,1)
(all,3)
(permission.,1)
("License");,1)
(written,2)
(generated,2)
(consequential,1)
(Derivative,17)
(AND,11)
(rights,3)
(http://www.apache.org/licenses/,1)
(terms.,1)
(Catholique,1)
(deliberate,1)
(entity.,2)
(Work,,4)
(special,,1)
(Additional,1)
(Legal,3)
(034819,1)
(least,1)
(text,4)
(on,11)
(editorial,1)
(redistributing,2)
("License",1)
(against,1)
(permission,1)
(9,1)
(separate,2)
(and/or,3)
(LICENSE,1)
(union,1)
((and,1)
(1,1)
(including,,1)
(Entity,3)
(negligent,1)
(LIABLE,2)
(IN,6)
(use,8)
(enclosed,2)
(contains,1)
(files,1)
(Entity",1)
(Work.,1)
(owner.,1)
(preferred,1)
(modifications,3)
(brackets!),1)
(available,1)
(code,5)
(http://www.apache.org/licenses/LICENSE-2.0,1)
(more,1)
(possibility,1)
(product,1)
(liable,1)
(SUCH,2)
(direction,1)
(must,8)
(making,1)
(Disclaimer,1)
(disclaimer.,2)
(Commission,1)
(OTHERWISE),2)
(Hadoop,1)
((an,1)
(APPENDIX:,1)
("Licensor",1)
(DISCLAIMED.,2)
("Derivative,1)
(elaborations,,1)
(incidental,,1)
(prepare,1)
(A,3)
(exercising,1)
(*/,3)
(which,2)
(pertain,2)
(explicitly,1)
(tort,1)
(3.,1)
(also,1)
(conversions,1)
(liability,2)
(whether,4)
(character,1)
(should,1)
(thereof.,1)
(of,,3)
(your,4)
(royalty-free,,2)
(entities,1)
(or,,1)
(NEGLIGENCE,2)
(author,1)
("Not,1)
(source,9)
(then,2)
((including,3)
(Redistribution.,1)
(attribution,4)
(by,21)
(TO,,4)
(defined,1)
(OWNER,2)
(If,2)
(an,6)
(/*,1)
(Collet.,1)
(improving,1)
(grossly,1)
(COPYRIGHT,4)
(above,,1)
(theory,,1)
(mailing,1)
(7.,1)
(Notwithstanding,1)
(code,,2)
(cross-claim,1)
(provide,1)
((such,1)
(arising,1)
(Object,4)
(In,1)
(-,7)
(those,3)
(work,,2)
(easier,1)
(based,1)
(medium,,1)
(within,8)
(worldwide,,2)
(authorship.,1)
(files.,1)
(inability,1)
(you,2)
(POSSIBILITY,2)
(cannot,1)
(copies,1)
(a,21)
(statement,1)
(above,4)
(state,1)
(work,5)
(by,,3)
(to,41)
(appear.,1)
(Your,9)
(where,1)
(liability.,1)
(governing,1)
(NOT,4)
(License,,6)
(hold,1)
(and,51)
(copyright,15)
(USE,,3)
(compliance,1)
(SOFTWARE,,2)
(comment,1)
(additional,4)
(executed,1)
(mechanical,1)
(Contributor,8)
[spark@S1PA222 ~]$

0
1
分享到:
评论

相关推荐

    02Spark编程模型和解析

    - **部署方式**: 包括Spark集群部署和Spark应用程序部署两种主要方式。 - **应用程序结构**: 由Driver程序和Executor组成。 - **Driver**: 主要负责应用程序的逻辑执行和RDD的创建。 - **Executor**: 负责执行任务...

    编程指南快速入门 - Spark 2.4.0文档.pdf

    - **计数**:`textFile.count()`返回数据集中元素的数量。 - **获取第一个元素**:`textFile.first()`返回数据集中的第一个元素。 - **过滤**:`textFile.filter(line => line.contains("Spark"))`返回包含指定...

    Spark 1.0.0 API (java)

    - **SparkContext**:Java程序的入口点,负责与Spark集群建立连接,创建RDD,并管理任务的执行。通过`SparkConf`配置实例化。 ```java SparkConf conf = new SparkConf().setAppName("MySparkApp").setMaster(...

    spark2.1.0 JAVA API

    JavaRDD<String> rdd = sc.textFile("hdfs://path/to/file"); ``` 3. **转换(Transformations)**: RDD上的算子,如`map()`, `filter()`, `reduceByKey()`, `groupByKey()`等,它们不立即执行,而是创建一个新的...

    sparkStreaming实战学习资料

    - **通过读取外部数据源**:如使用`sc.textFile("hdfs://path/to/file")`来从HDFS中读取文本文件。 - **从现有集合转换**:也可以使用`sc.parallelize(List(...))`直接从程序中的集合创建RDD,这种方式通常用于测试...

    spark1.1快速上手

    在文档中,通过`val frdd = sc.textFile("hdfs://sparkMaster:9000/wordcount/in/word.txt")`创建了一个RDD。这个RDD是通过读取HDFS上的文本文件生成的,`sc`是SparkContext的实例,它是进入Spark的主要入口点。创建...

    spark下实现wordcount

    此配置对于集群模式运行 Spark 应用至关重要。 ##### 3. 准备输入文件 在 HDFS 上创建输入文件目录,并将文本文件上传至 HDFS: ```bash hdfs dfs -mkdir /a hdfs dfs -put '/home/hadoop/one.txt' /a ``` 其中 ...

    Spark及pyspark的操作应用.pdf

    logData = sc.textFile(logFile, 2).cache() numAs = logData.filter(lambda line: 'a' in line).count() numBs = logData.filter(lambda line: 'b' in line).count() print('Lines with a: %s, Lines with b: %s' %...

    SparkCore快速入门详解

    3. **加载数据**:使用`SparkContext`的`textFile()`方法读取数据,如HDFS、本地文件系统或任何其他Hadoop支持的源。 4. **数据处理**:应用RDD转换和行动,如`map()`、`filter()`、`reduce()`等,构建数据处理逻辑...

    RDD编程初级实践数据集

    通过这个“RDD编程初级实践数据集”,初学者可以动手操作,学习如何在Spark中创建、转换和操作RDD,以及理解其容错机制和性能优化策略。实践中遇到的问题和解决方案将有助于深入理解Spark的工作原理和最佳实践。

    SparkCESHI版代码

    在“SparkCESHI版代码”中,我们可能看到如何创建和操作RDD,例如使用`parallelize`或`textFile`方法读取和创建数据,然后应用转换(如`map`、`filter`)和行动(如`count`、`saveAsTextFile`)操作。此外,可能还会...

    playing-with-spark-rdd:Apache Spark RDD示例

    例如,`SparkContext.textFile()`函数用于从HDFS、本地文件系统或其他Hadoop支持的文件系统读取文本文件。 2. **基本操作**:包括`count()`(计算元素数量)、`filter()`(根据条件过滤元素)、`map()`(应用函数到...

    keyword.txt用来做关键日UV统计的测试数据

    - **数据加载**:首先将数据加载到Spark集群中,可以通过多种方式实现,例如HDFS、S3等。 - **数据转换**:利用Spark提供的API对数据进行转换处理,例如`map`、`filter`等操作。 - **聚合计算**:对处理后的数据...

    PyCharm+PySpark远程调试的环境配置的方法

    logData = sc.textFile("hdfs://master:9000/README.md").cache() numAs = logData.filter(lambda s: 'a' in s).count() numBs = logData.filter(lambda s: 'b' in s).count() print("Lines with a: %i, lines ...

    RDD-

    这些数据分布在Spark集群的不同节点上,可以执行并行计算。RDD是基于静态图模型,这个图表示了数据的转换过程,使得Spark可以在容错和优化执行计划方面表现出色。 **二、RDD的创建** RDD可以通过两种方式创建:一...

    pyspark-examples

    通过`sc.parallelize()`或`sc.textFile()`创建RDD。 2. **转换(Transformations)**:如`map()`, `filter()`, `reduceByKey()`等,它们不会立即执行,而是生成一个新的RDD。 3. **行动(Actions)**:如`collect...

Global site tag (gtag.js) - Google Analytics