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Convert java methods to static
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Mahmoud Hanafy committed May 20, 2016
1 parent e792bb3 commit a252514
Showing 1 changed file with 21 additions and 21 deletions.
42 changes: 21 additions & 21 deletions src/main/java/com/highperformancespark/examples/dataframe/JavaHappyPandas.java
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Original file line number Diff line number Diff line change
Expand Up @@ -19,23 +19,23 @@ public class JavaHappyPandas {
/**
* Creates SQLContext with an existing SparkContext.
*/
public SQLContext sqlContext(JavaSparkContext jsc) {
public static SQLContext sqlContext(JavaSparkContext jsc) {
SQLContext sqlContext = new SQLContext(jsc);
return sqlContext;
}

/**
* Creates HiveContext with an existing SparkContext.
*/
public HiveContext hiveContext(JavaSparkContext jsc) {
public static HiveContext hiveContext(JavaSparkContext jsc) {
HiveContext hiveContext = new HiveContext(jsc);
return hiveContext;
}

/**
* Illustrate loading some JSON data.
*/
public DataFrame loadDataSimple(JavaSparkContext jsc, SQLContext sqlContext, String path) {
public static DataFrame loadDataSimple(JavaSparkContext jsc, SQLContext sqlContext, String path) {
DataFrame df1 = sqlContext.read().json(path);

DataFrame df2 = sqlContext.read().format("json").option("samplingRatio", "1.0").load(path);
Expand All @@ -46,7 +46,7 @@ public DataFrame loadDataSimple(JavaSparkContext jsc, SQLContext sqlContext, Str
return df1;
}

public DataFrame jsonLoadFromRDD(SQLContext sqlContext, JavaRDD<String> input) {
public static DataFrame jsonLoadFromRDD(SQLContext sqlContext, JavaRDD<String> input) {
JavaRDD<String> rdd = input.filter(e -> e.contains("panda"));
DataFrame df = sqlContext.read().json(rdd);
return df;
Expand All @@ -60,7 +60,7 @@ public DataFrame jsonLoadFromRDD(SQLContext sqlContext, JavaRDD<String> input) {
* @param pandaInfo the input DataFrame
* @return Returns DataFrame of (place, percentage of happy pandas)
*/
public DataFrame happyPandasPercentage(DataFrame pandaInfo) {
public static DataFrame happyPandasPercentage(DataFrame pandaInfo) {
DataFrame happyPercentage = pandaInfo.select(pandaInfo.col("place"),
pandaInfo.col("happyPandas").divide(pandaInfo.col("totalPandas")).as("percentHappy"));
return happyPercentage;
Expand All @@ -72,7 +72,7 @@ public DataFrame happyPandasPercentage(DataFrame pandaInfo) {
* @param pandaInfo the input DataFrame
* @return Returns a DataFrame of pandaId and integer value for pandaType.
*/
public DataFrame encodePandaType(DataFrame pandaInfo) {
public static DataFrame encodePandaType(DataFrame pandaInfo) {
DataFrame encodedDF = pandaInfo.select(pandaInfo.col("id"),
when(pandaInfo.col("pt").equalTo("giant"), 0).
when(pandaInfo.col("pt").equalTo("red"), 1).
Expand All @@ -84,21 +84,21 @@ public DataFrame encodePandaType(DataFrame pandaInfo) {
/**
* Gets places with happy pandas more than minHappinessBound.
*/
public DataFrame minHappyPandas(DataFrame pandaInfo, int minHappyPandas) {
public static DataFrame minHappyPandas(DataFrame pandaInfo, int minHappyPandas) {
return pandaInfo.filter(pandaInfo.col("happyPandas").geq(minHappyPandas));
}

/**
* Find pandas that are sad.
*/
public DataFrame sadPandas(DataFrame pandaInfo) {
public static DataFrame sadPandas(DataFrame pandaInfo) {
return pandaInfo.filter(pandaInfo.col("happy").notEqual(true));
}

/**
* Find pandas that are happy and fuzzier than squishy.
*/
public DataFrame happyFuzzyPandas(DataFrame pandaInfo) {
public static DataFrame happyFuzzyPandas(DataFrame pandaInfo) {
DataFrame df = pandaInfo.filter(
pandaInfo.col("happy").and(pandaInfo.col("attributes").apply(0)).gt(pandaInfo.col("attributes").apply(1))
);
Expand All @@ -109,31 +109,31 @@ public DataFrame happyFuzzyPandas(DataFrame pandaInfo) {
/**
* Gets places that contains happy pandas more than unhappy pandas.
*/
public DataFrame happyPandasPlaces(DataFrame pandaInfo) {
public static DataFrame happyPandasPlaces(DataFrame pandaInfo) {
return pandaInfo.filter(pandaInfo.col("happyPandas").geq(pandaInfo.col("totalPandas").divide(2)));
}

/**
* Remove duplicate pandas by id.
*/
public DataFrame removeDuplicates(DataFrame pandas) {
public static DataFrame removeDuplicates(DataFrame pandas) {
DataFrame df = pandas.dropDuplicates(new String[]{"id"});
return df;
}

public DataFrame describePandas(DataFrame pandas) {
public static DataFrame describePandas(DataFrame pandas) {
return pandas.describe();
}

public DataFrame maxPandaSizePerZip(DataFrame pandas) {
public static DataFrame maxPandaSizePerZip(DataFrame pandas) {
return pandas.groupBy(pandas.col("zip")).max("pandaSize");
}

public DataFrame minMaxPandaSizePerZip(DataFrame pandas) {
public static DataFrame minMaxPandaSizePerZip(DataFrame pandas) {
return pandas.groupBy(pandas.col("zip")).agg(min("pandaSize"), max("pandaSize"));
}

public DataFrame minPandaSizeMaxAgePerZip(DataFrame pandas) {
public static DataFrame minPandaSizeMaxAgePerZip(DataFrame pandas) {
Map<String, String> map = new HashMap<>();
map.put("pandaSize", "min");
map.put("age", "max");
Expand All @@ -142,11 +142,11 @@ public DataFrame minPandaSizeMaxAgePerZip(DataFrame pandas) {
return df;
}

public DataFrame minMeanSizePerZip(DataFrame pandas) {
public static DataFrame minMeanSizePerZip(DataFrame pandas) {
return pandas.groupBy(pandas.col("zip")).agg(min(pandas.col("pandaSize")), mean(pandas.col("pandaSize")));
}

public DataFrame simpleSqlExample(DataFrame pandas) {
public static DataFrame simpleSqlExample(DataFrame pandas) {
SQLContext sqlContext = pandas.sqlContext();
pandas.registerTempTable("pandas");

Expand All @@ -159,11 +159,11 @@ public DataFrame simpleSqlExample(DataFrame pandas) {
* Pandas will be sorted by "size" first and if two pandas
* have the same "size" will be sorted by "age".
*/
public DataFrame orderPandas(DataFrame pandas) {
public static DataFrame orderPandas(DataFrame pandas) {
return pandas.orderBy(pandas.col("pandaSize").asc(), pandas.col("age").desc());
}

public DataFrame computeRelativePandaSizes(DataFrame pandas) {
public static DataFrame computeRelativePandaSizes(DataFrame pandas) {
//tag::relativePandaSizesWindow[]
WindowSpec windowSpec = Window
.orderBy(pandas.col("age"))
Expand All @@ -179,7 +179,7 @@ public DataFrame computeRelativePandaSizes(DataFrame pandas) {
//end::relativePandaSizesQuery[]
}

public void joins(DataFrame df1, DataFrame df2) {
public static void joins(DataFrame df1, DataFrame df2) {
//tag::innerJoin[]
// Inner join implicit
df1.join(df2, df1.col("name").equalTo(df2.col("name")));
Expand All @@ -203,7 +203,7 @@ public void joins(DataFrame df1, DataFrame df2) {
//end::leftsemiJoin[]
}

public DataFrame selfJoin(DataFrame df) {
public static DataFrame selfJoin(DataFrame df) {
return df.as("a").join(df.as("b")).where(df.col("name").equalTo(df.col("name")));
}

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