example changes so they convert to notebooks better

EclairJS · Apr 15, 2016 · a64ae21 · a64ae21
1 parent 1f285f2
commit a64ae21
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Showing 8 changed files with 23 additions and 38 deletions.
diff --git a/examples/accumulator.js b/examples/accumulator.js
@@ -20,7 +20,7 @@
  */
 
 
-var run = function(sc){
+function run(sc){
 
 	sc.parallelize([1, 2, 3, 4]).foreach(function(x, accum) {
 		accum.add(x);

diff --git a/examples/mllib/fp_growth_example.js b/examples/mllib/fp_growth_example.js
@@ -46,20 +46,10 @@ function run(sc, useTake) {
  check if SparkContext is defined, if it is we are being run from Unit Test
  */
 var inputFile = ((typeof args !== "undefined") && (args.length > 1)) ? args[1] : "examples/data/mllib/sample_fpgrowth.txt";
-var minSupport = 0.3;
-var numPartition = -1;
+var minSupport = ((typeof args !== "undefined") && (args.length > 2)) ? parseFloat(args[2]) :0.3;
+var numPartition = ((typeof args !== "undefined") && (args.length > 3)) ? parseInt(args[3]) : -1;
 
 if (typeof sparkContext === 'undefined') {
-    if (args.length >= 2) {
-        inputFile = args[1];
-    }
-
-    if (args.length >= 3) {
-        minSupport = parseFloat(args[2]);
-    }
-    if (args.length >= 4) {
-        numPartition = parseInt(args[3]);
-    }
 
     var sparkConf = new SparkConf().setAppName("FPGrowthExample");
     var sc = new SparkContext(sparkConf);

diff --git a/examples/mllib/power_iteration_clustering_example.js b/examples/mllib/power_iteration_clustering_example.js
@@ -46,8 +46,8 @@ if (typeof sparkContext === 'undefined') {
 
     var sparkConf = new SparkConf().setAppName("PowerIterationClusteringExample");
     var sc = new SparkContext(sparkConf);
-    var results = run(sc);
-    results.forEach(function(a){
+    var result = run(sc);
+    result.forEach(function(a){
         print(a.id() + " -> " + a.cluster());
     });
 

diff --git a/examples/mllib/prefix_span_example.js b/examples/mllib/prefix_span_example.js
@@ -45,8 +45,8 @@ if (typeof sparkContext === 'undefined') {
 
     var sparkConf = new SparkConf().setAppName("PrefixSpanExample");
     var sc = new SparkContext(sparkConf);
-    var results = run(sc);
-    results.forEach(function (freqSeq) {
+    var result = run(sc);
+    result.forEach(function (freqSeq) {
         print(JSON.stringify(freqSeq.sequence()) + ", " + freqSeq.freq());
     });
 

diff --git a/examples/mllib/recommendation_example.js b/examples/mllib/recommendation_example.js
@@ -70,10 +70,10 @@ if (typeof sparkContext === 'undefined') {
 
     var sparkConf = new SparkConf().setAppName("Collaborative Filtering Example");
     var sc = new SparkContext(sparkConf);
-    var results = run(sc);
-    print("Mean Squared Error = " + results.MSE);
+    var result = run(sc);
+    print("Mean Squared Error = " + result.MSE);
     // Save and load model
-    results.model.save(sc, "target/tmp/myCollaborativeFilter");
+    result.model.save(sc, "target/tmp/myCollaborativeFilter");
     var sameModel = MatrixFactorizationModel.load(sc,
         "target/tmp/myCollaborativeFilter");
 

diff --git a/examples/mllib/svd_example.js b/examples/mllib/svd_example.js
@@ -50,13 +50,13 @@ if (typeof sparkContext === 'undefined') {
 
     var sparkConf = new SparkConf().setAppName("SVD Example");
     var sc = new SparkContext(sparkConf);
-    var results = run(sc);
+    var result = run(sc);
     print("U factor is:");
-    results.collectPartitions.forEach(function (vector) {
+    result.collectPartitions.forEach(function (vector) {
         print("\t" + vector);
     });
-    print("Singular values are: " + results.s);
-    print("V factor is:\n" + results.V);
+    print("Singular values are: " + result.s);
+    print("V factor is:\n" + result.V);
 
     sc.stop();
 }

diff --git a/examples/mllib/svm_with_sgd_example.js b/examples/mllib/svm_with_sgd_example.js
@@ -61,11 +61,11 @@ if (typeof sparkContext === 'undefined') {
 
     var sparkConf = new SparkConf().setAppName("SVMWithSGDExample");
     var sc = new SparkContext(sparkConf);
-    var results = run(sc);
-    print("Area under ROC = " + results.auROC);
+    var result = run(sc);
+    print("Area under ROC = " + result.auROC);
 
 // Save and load model
-    results.model.save(sc, "target/tmp/SVMWithSGDModel");
+    result.model.save(sc, "target/tmp/SVMWithSGDModel");
     var sameModel = SVMModel.load(sc, "target/tmp/SVMWithSGDModel");
 
     sc.stop();

diff --git a/examples/spark_lr.js b/examples/spark_lr.js
@@ -19,23 +19,18 @@
  bin/eclairjs.sh examples/spark_lr.js"
  */
 
-function showWarning() {
-    var warning = "WARN: This is a naive implementation of Logistic Regression " +
-        "and is given as an example!\n" +
-        "Please use either org.apache.spark.mllib.classification.LogisticRegressionWithSGD " +
-        "or org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS " +
-        "for more conventional use.";
-    print(warning);
-}
+/*  WARNING: This is a naive implementation of Logistic Regression
+         and is given as an example!
+         Please use either org.apache.spark.mllib.classification.LogisticRegressionWithSGD
+         or org.apache.spark.mllib.classification.LogisticRegressionWithLBFGS
+         for more conventional use.
+*/
 
 function printWeights(a) {
     print(a);
 }
 
 
-showWarning();
-
-
 var D = 10;   // Number of dimensions
 
 var    file = (args.length > 1) ? args[1] : "./examples/data/lr_data.txt";