要保持简单,可能要在DataSet 中为每个DataTable创建一个DataAdapter。 To maintain simplicity, you may want to create a DataAdapter for each DataTable in your DataSet. 一个例外是DataSet ,它对多个阅读器是线程安全的。 The one exception is the DataSet , which is thread-safe for multiple readers.DataSet 的另一个好处是可被继承以创建一个强类型DataSet。Another benefit of the DataSet is that it can be inherited to create a strongly typed DataSet. . 统一Scala和Java中DataFrames和Datasets:从Spark2.0开始,DataFrame只是Dataset ofRow的类型别名。 Unifying DataFrames and Datasets in Scala/Java: Starting in Spark 2.0, DataFrame is just a type alias for Dataset of Row. 生成Guid值的算法应该永远不会使数据源中生成的Guid值与DataSet 中生成的Guid值一样。 The algorithm that generates Guid values should never generate the same Guid in the DataSet as is generated by the data source.
由于编译时类型安全性在Python和R中并不是语言特性,因此Dataset 的概念不适用于这些语言API。 Since compile-time type-safety in Python and R is not a language feature, the concept of Dataset does not apply to these languages' APIs. NET提供以下两个对象,用于检索关系数据并将其存储在内存中:DataSet 和DataReader。 NET provides two objects for retrieving relational data and storing it in memory: the DataSet and the DataReader. 有几种方式可以跟SparkSQL进行交互,包括SQL和Dataset API。 There are several ways to interact with Spark SQL including SQL and the Dataset API. 统一Scala和Java中DataFrames和Datasets的API:从Spark2.0开始,DataFrame仅仅是Dataset 的一个别名。 Unifying DataFrames and Datasets in Scala/Java: Starting in Spark 2.0, DataFrame is just a type alias for Dataset of Row. 类型化DataSet从DataSet 类派生,因此不会牺牲DataSet的任何功能。 A typed DataSet derives from the DataSet class, so that you do not sacrifice any of the DataSet functionality. 与之形成对比,Dataset 就是一些有明确类型定义的JVM对象的集合,通过你在Scala中定义的CaseClass或者Java中的Class来指定。 Dataset , by contrast, is a collection of strongly-typed JVM objects, dictated by a case class you define, in Scala or Java.GRUN:Anobservations-basedglobalgriddedrunoffdataset from1902to2014/GRUN:从1902年到2014年的基于观测的全球网格化径流数据集. GRUN: an observation-based global gridded runoff dataset from 1902 to 2014 GRUN: an observation-based global gridded runoff dataset from 1902 to 2014 Gionata Ghiggi et al. 这些数据集工具(例如DataSet Wizard,DataSetEditor,DataSetManager),使您创建和编辑类型化和非类型化的数据集更简便。 DataSet tools, such as DataSet Wizard, DataSet Editor, DataSet Manager, provide you an easy way to create and edit typed and untyped DataSets. .有类型的方法(typedmethods)(比如:map,filter,groupByKey)和无类型的方法(untypedmethods)(比如:select,groupBy)目前在Dataset 类上可用。 Both the typed methods(e.g. map, filter, groupByKey) and the untyped methods(e.g. select, groupBy) are available on the Dataset class. 在[Hoyer,2004][2]中已经观察到,当被小心约束时,NMF可以产生数据集的基于部分的表式(parts-basedrepresentationofthedataset ),能够产生可解释的模型(interpretablemodels)。 It has been observed in[Hoyer, 2004][2] that, when carefully constrained, NMF can produce a parts-based representation of the dataset , resulting in interpretable models. 我们的算法系统在挑战“法国街道名称识别数据集”(FrenchStreetNameSigns(FSNS)dataset )中达到了84.2%的正确率,明显优于之前的最优系统。 Our algorithm achieves 84.2% accuracy on the challenging French Street Name Signs(FSNS) dataset , significantly outperforming the previous state-of-the-art systems. 因为dataset 被同样的分区了,在一个单独的rdd1的partition中的一组key都可以仅出现在rdd2的一个单独的partition中。 Because the datasets are partitioned identically, the set of keys in any single partition of rdd1 can only occur in a single partition of rdd2. 因为编译时类型安全(compile-timetype-safety)在Python和R中并不是语言特性,所以Dataset 的概念并不在这些语言中提供相应的API。 Since compile-time type-safety in Python and R is not a language feature, the concept of Dataset does not apply to these languages' APIs. The Pima Indians Diabetes Dataset . Then use the tf. data. Dataset .
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