DataFrame/SQL/Hive 在DataFrameAPI方面,实现了新的聚合函数接口AggregateFunction2以及7个相应的build-in的聚合函数,同时基于新接口实现了相应的UDAF接口。新的聚合函数接口把一个聚合函数拆解为三个动作: initialize/update/merge,然后用户只需要定义其中的逻辑既可以实现不同的聚合函数功能。Spark的这个新的聚合函数实现...
[root@hadoop1 hadoop]# ssh-keygen Generatingpublic/privatersa key pair.Enter fileinwhich to save thekey(/root/.ssh/id_rsa):Enterpassphrase(emptyforno passphrase):Enter same passphrase again:Your identification has been savedin/root/.ssh/id_rsa.Yourpublickey has been savedin/root/.ssh/id_...
* Create an RDD for non-bucketed reads. * The bucketed variant of this function is [[createBucketedReadRDD]]. * * @param readFile a function to read each (part of a) file. * @param selectedPartitions Hive-style partition that are part of the read. * @param fsRelation [[HadoopFsR...
<dependencies> <dependency> <groupId>org.apache.spark</groupId> <artifactId>spark-core_2.11</artifactId> <version>2.1.1</version> </dependency> </dependencies> <build> <plugins> <plugin> <groupId>net.alchim31.maven</groupId> <artifactId>scala-maven-plugin</artifactId> <version>3.4.6</...
首先在项目的pom文件中添加build配置,和dependencies标签平级 <build> <plugins> <!-- java编译插件 --> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-compiler-plugin</artifactId> <version>3.6.0</version> <configuration> 1.8 <target>1.8</target> <encoding>UTF-8</encodin...
s.copy(child = p2.copy(projectList = buildCleanedProjectList(l1, p2.projectList))) } } 第二个主要优化的点是针对序列化的优化,上述filter的逻辑计划会涉及到RDD数据的反序列化和序列化,但是后面的map阶段又会进行数据的序列化和反序列化,但其实数据类型始终没变,所以这只需要一次反序列化和序列化就够...
[5]) return LabeledDocument((values[6]), textValue, hot) # Load the raw HVAC.csv file, parse it using the function data = sc.textFile("/HdiSamples/HdiSamples/SensorSampleData/hvac/HVAC.csv") documents = data.filter(lambda s: "Date" not in s).map(parseDocument) training = documents...
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在ParquetFileFormat#buildReaderWithPartitionValues实现中, 会使用 split 来初始化 reader, 并且根据配置可以把 reader 分为否是 vectorized 的: vectorizedReader.initialize(split, hadoopAttemptContext) reader.initialize(split, hadoopAttemptContext) 关于 步骤2 在画外中还有更详细的代码, 但与本文的主流程关系不...
* submitJob. Each Job may require the execution of multiple stages to build intermediate data. * * - Stages ([[Stage]]) are sets of tasks that compute intermediate results in jobs, where each * task computes the same function on partitions of the same RDD. Stages are separated at shuffle...