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#include <cstdio>
#include <utility>
#include <cmath>
#include <string>
#include <vector>
#include <algorithm>
using namespace std;
struct TrackingEvent {
package com.ta.geo.calculation
import com.holdenkarau.spark.testing.DataFrameSuiteBase
import com.ta.geo.calculation.GeodistanceCalculation.matchTrackingEventsWithNearestAirport
import com.ta.geo.datasource.ModelDatasource
import com.ta.geo.measure.{DistanceMeasure, HaversineDistance}
import com.ta.geo.model.{Airport, TrackingEvent}
import org.apache.spark.sql.{Dataset, SparkSession}
import org.scalatest.{FlatSpec, Matchers}
import json
from abc import ABCMeta, abstractmethod
from pyspark import SQLContext, SparkContext
from pyspark.sql import DataFrame
class AbstractSQLConnector(metaclass=ABCMeta):
@classmethod
def load_config(cls, vendor: str, config_instance: str, config_path: str) -> (str, str):
/**
* Column-major dense matrix.
* The entry values are stored in a single array of doubles with columns listed in sequence.
* For example, the following matrix
* {{{
* 1.0 2.0
* 3.0 4.0
* 5.0 6.0
* }}}
* is stored as `[1.0, 3.0, 5.0, 2.0, 4.0, 6.0]`.
@fpopic
fpopic / Matrice.java
Last active September 13, 2017 15:29
List<Vector> local = A.toRowMatrix().rows().toJavaRDD().collect();
int M = (int) A.numRows();
int N = (int) A.numCols();
double[] arr = new double[M * N];
for (int i = 0; i < M; i++) {
for (int j = 0; j < N; j++) {
arr[i * N + j] = local.get(i).apply(j);
}
List<Vector> local = A.toRowMatrix().rows().toJavaRDD().collect();
int M = (int) A.numRows();
int N = (int) A.numCols();
// List<Double> -> double[]
double[] arr = new double[M * N];
for (int i = 0; i < M; i++) {
for (int j = 0; j < N; j++) {
arr[i * N + j] = local.get(i).apply(j);
// indexed row matrix
IndexedRowMatrix A = new IndexedRowMatrix(rddA.rdd());
List<Double> stream = A.toRowMatrix().rows().toJavaRDD()
// double[][] -> List<Double>
.flatMap(v -> Arrays.stream(v.toArray()).boxed().iterator())
.collect();
// List<Double> -> double[]
package com
import org.apache.spark.mllib.linalg
import org.apache.spark.mllib.linalg.Vectors
import org.apache.spark.mllib.linalg.distributed.RowMatrix
import org.apache.spark.rdd.RDD
import org.apache.spark.sql.SparkSession
object CollectTest {
def main(args: Array[String]): Unit = {
package com
import scala.collection.mutable
// T must implement expand() method
trait Expandable[T] {
def expand(): Traversable[T]
}
case class BFSNode[T](node: T, price: Int, parent: Option[BFSNode[T]]) extends Ordered[BFSNode[T]] {

%AddDeps org.vegas-viz vegas_2.11 0.3.11 --repository file:/home/<USER>/.ivy2/cache

-> file:/tmp/toree-tmp-dir6402005190510739766/toree_add_deps/
-> file:/home/fpopic/.ivy2/cache
-> https://repo1.maven.org/maven2
=> https://repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/vegas_2.11-0.3.11.pom: Found at /tmp/toree-tmp-dir6402005190510739766/toree_add_deps/https/repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/vegas_2.11-0.3.11.pom
=> https://repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/vegas_2.11-0.3.11.pom.sha1: Found at /tmp/toree-tmp-dir6402005190510739766/toree_add_deps/https/repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/vegas_2.11-0.3.11.pom.sha1
=> https://repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/: Found at /tmp/toree-tmp-dir6402005190510739766/toree_add_deps/https/repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/.directory
=> https://repo1.maven.org/maven2/org/vegas-viz/vegas_2.11/0.3.11/vegas_2.11-0.3.11.pom.sha1: Found at /tmp/toree-tmp-di