本文整理汇总了Java中org.apache.spark.rdd.RDD.toLocalIterator方法的典型用法代码示例。如果您正苦于以下问题：Java RDD.toLocalIterator方法的具体用法？Java RDD.toLocalIterator怎么用？Java RDD.toLocalIterator使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.apache.spark.rdd.RDD的用法示例。
在下文中一共展示了RDD.toLocalIterator方法的9个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: testOutputRDDStringIJVDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringIJVDML() {
System.out.println("MLContextTest - output RDD String IJV DML");
String s = "M = matrix('1 2 3 4', rows=2, cols=2);";
Script script = dml(s).out("M");
MLResults results = ml.execute(script);
RDD<String> rddStringIJV = results.getRDDStringIJV("M");
Iterator<String> iterator = rddStringIJV.toLocalIterator();
Assert.assertEquals("1 1 1.0", iterator.next());
Assert.assertEquals("1 2 2.0", iterator.next());
Assert.assertEquals("2 1 3.0", iterator.next());
Assert.assertEquals("2 2 4.0", iterator.next());
}
示例2: testOutputRDDStringIJVPYDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringIJVPYDML() {
System.out.println("MLContextTest - output RDD String IJV PYDML");
String s = "M = full('1 2 3 4', rows=2, cols=2)";
Script script = pydml(s).out("M");
MLResults results = ml.execute(script);
RDD<String> rddStringIJV = results.getRDDStringIJV("M");
Iterator<String> iterator = rddStringIJV.toLocalIterator();
Assert.assertEquals("1 1 1.0", iterator.next());
Assert.assertEquals("1 2 2.0", iterator.next());
Assert.assertEquals("2 1 3.0", iterator.next());
Assert.assertEquals("2 2 4.0", iterator.next());
}
示例3: testOutputRDDStringCSVDenseDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringCSVDenseDML() {
System.out.println("MLContextTest - output RDD String CSV Dense DML");
String s = "M = matrix('1 2 3 4', rows=2, cols=2); print(toString(M));";
Script script = dml(s).out("M");
MLResults results = ml.execute(script);
RDD<String> rddStringCSV = results.getRDDStringCSV("M");
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0", iterator.next());
Assert.assertEquals("3.0,4.0", iterator.next());
}
示例4: testOutputRDDStringCSVDensePYDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringCSVDensePYDML() {
System.out.println("MLContextTest - output RDD String CSV Dense PYDML");
String s = "M = full('1 2 3 4', rows=2, cols=2)\nprint(toString(M))";
Script script = pydml(s).out("M");
MLResults results = ml.execute(script);
RDD<String> rddStringCSV = results.getRDDStringCSV("M");
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0", iterator.next());
Assert.assertEquals("3.0,4.0", iterator.next());
}
示例5: testOutputRDDStringCSVSparseDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringCSVSparseDML() {
System.out.println("MLContextTest - output RDD String CSV Sparse DML");
String s = "M = matrix(0, rows=10, cols=10); M[1,1]=1; M[1,2]=2; M[2,1]=3; M[2,2]=4; print(toString(M));";
Script script = dml(s).out("M");
MLResults results = ml.execute(script);
RDD<String> rddStringCSV = results.getRDDStringCSV("M");
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0", iterator.next());
Assert.assertEquals("3.0,4.0", iterator.next());
}
示例6: testOutputRDDStringCSVSparsePYDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringCSVSparsePYDML() {
System.out.println("MLContextTest - output RDD String CSV Sparse PYDML");
String s = "M = full(0, rows=10, cols=10)\nM[0,0]=1\nM[0,1]=2\nM[1,0]=3\nM[1,1]=4\nprint(toString(M))";
Script script = pydml(s).out("M");
MLResults results = ml.execute(script);
RDD<String> rddStringCSV = results.getRDDStringCSV("M");
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0", iterator.next());
Assert.assertEquals("3.0,4.0", iterator.next());
}
示例7: testOutputMatrixObjectDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputMatrixObjectDML() {
System.out.println("MLContextTest - output matrix object DML");
String s = "M = matrix('1 2 3 4', rows=2, cols=2);";
MatrixObject mo = ml.execute(dml(s).out("M")).getMatrixObject("M");
RDD<String> rddStringCSV = MLContextConversionUtil.matrixObjectToRDDStringCSV(mo);
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0", iterator.next());
Assert.assertEquals("3.0,4.0", iterator.next());
}
示例8: testOutputMatrixObjectPYDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputMatrixObjectPYDML() {
System.out.println("MLContextTest - output matrix object PYDML");
String s = "M = full('1 2 3 4', rows=2, cols=2);";
MatrixObject mo = ml.execute(pydml(s).out("M")).getMatrixObject("M");
RDD<String> rddStringCSV = MLContextConversionUtil.matrixObjectToRDDStringCSV(mo);
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0", iterator.next());
Assert.assertEquals("3.0,4.0", iterator.next());
}
示例9: testOutputRDDStringCSVFromMatrixDML
import org.apache.spark.rdd.RDD; //导入方法依赖的package包/类
@Test
public void testOutputRDDStringCSVFromMatrixDML() {
System.out.println("MLContextTest - output RDD String CSV from matrix DML");
String s = "M = matrix('1 2 3 4', rows=1, cols=4);";
Script script = dml(s).out("M");
RDD<String> rddStringCSV = ml.execute(script).getMatrix("M").toRDDStringCSV();
Iterator<String> iterator = rddStringCSV.toLocalIterator();
Assert.assertEquals("1.0,2.0,3.0,4.0", iterator.next());
}