#Java - Code Snippets for '#.Logs' - 9 code snippet(s) found |
|
Sample 1. Code Sample / Example / Snippet of org.apache.calcite.rel.logical.LogicalProject | |
|
public RelNode convert(RelNode rel) {
final LogicalProject project = (LogicalProject) rel;
final RelTraitSet traitSet = project.getTraitSet().replace(out);
return new MongoProject(project.getCluster(), traitSet,
convert(project.getInput(), out), project.getProjects(),
project.getRowType());
}
|
|
Like Feedback org.apache.calcite.rel.logical.LogicalProject |
|
|
Sample 2. Code Sample / Example / Snippet of org.apache.spark.ml.classification.LogisticRegressionModel | |
|
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("JavaLogisticRegressionWithElasticNetExample");
JavaSparkContext jsc = new JavaSparkContext(conf);
SQLContext sqlContext = new SQLContext(jsc);
DataFrame training = sqlContext.read().format("libsvm")
.load("data/mllib/sample_libsvm_data.txt");
LogisticRegression lr = new LogisticRegression()
.setMaxIter(10)
.setRegParam(0.3)
.setElasticNetParam(0.8);
LogisticRegressionModel lrModel = lr.fit(training);
System.out.println("Coefficients: "
+ lrModel.coefficients() + " Intercept: " + lrModel.intercept());
jsc.stop();
}
|
|
Like Feedback org.apache.spark.ml.classification.LogisticRegressionModel |
|
|
Sample 3. Code Sample / Example / Snippet of org.apache.spark.ml.classification.LogisticRegression | |
|
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("JavaLogisticRegressionWithElasticNetExample");
JavaSparkContext jsc = new JavaSparkContext(conf);
SQLContext sqlContext = new SQLContext(jsc);
DataFrame training = sqlContext.read().format("libsvm")
.load("data/mllib/sample_libsvm_data.txt");
LogisticRegression lr = new LogisticRegression()
.setMaxIter(10)
.setRegParam(0.3)
.setElasticNetParam(0.8);
LogisticRegressionModel lrModel = lr.fit(training);
System.out.println("Coefficients: "
+ lrModel.coefficients() + " Intercept: " + lrModel.intercept());
jsc.stop();
}
|
|
Like Feedback org.apache.spark.ml.classification.LogisticRegression |
|
|
Sample 4. Code Sample / Example / Snippet of org.apache.spark.mllib.classification.LogisticRegressionModel | |
|
public static void main(String[] args) {
SparkConf conf = new SparkConf().setAppName("JavaLogisticRegressionWithElasticNetExample");
JavaSparkContext jsc = new JavaSparkContext(conf);
SQLContext sqlContext = new SQLContext(jsc);
DataFrame training = sqlContext.read().format("libsvm")
.load("data/mllib/sample_libsvm_data.txt");
LogisticRegression lr = new LogisticRegression()
.setMaxIter(10)
.setRegParam(0.3)
.setElasticNetParam(0.8);
LogisticRegressionModel lrModel = lr.fit(training);
System.out.println("Coefficients: "
+ lrModel.coefficients() + " Intercept: " + lrModel.intercept());
jsc.stop();
}
|
|
Like Feedback org.apache.spark.mllib.classification.LogisticRegressionModel |
|
|
|
Sample 5. Code Sample / Example / Snippet of org.apache.calcite.rel.logical.LogicalFilter | |
|
public RelNode convert(RelNode rel) {
final LogicalFilter filter = (LogicalFilter) rel;
final RelTraitSet traitSet = filter.getTraitSet().replace(out);
return new MongoFilter(
rel.getCluster(),
traitSet,
convert(filter.getInput(), out),
filter.getCondition());
}
|
|
Like Feedback org.apache.calcite.rel.logical.LogicalFilter |
|
|
Sample 6. Code Sample / Example / Snippet of org.apache.calcite.rel.logical.LogicalAggregate | |
|
public RelNode convert(RelNode rel) {
final LogicalAggregate agg = (LogicalAggregate) rel;
final RelTraitSet traitSet =
agg.getTraitSet().replace(out);
try {
return new MongoAggregate(
rel.getCluster(),
traitSet,
convert(agg.getInput(), traitSet.simplify()),
agg.indicator,
agg.getGroupSet(),
agg.getGroupSets(),
agg.getAggCallList());
} catch (InvalidRelException e) {
LOGGER.warn(e.toString());
return null;
}
}
|
|
Like Feedback org.apache.calcite.rel.logical.LogicalAggregate |
|
|
Sample 7. Code Sample / Example / Snippet of org.apache.calcite.rel.logical.LogicalValues | |
|
private MongoValuesRule(MongoConvention out) {
super(
LogicalValues.class,
Convention.NONE,
out,
"MongoValuesRule");
}
@Override public RelNode convert(RelNode rel) {
LogicalValues valuesRel = (LogicalValues) rel;
return new MongoValuesRel(
valuesRel.getCluster(),
valuesRel.getRowType(),
valuesRel.getTuples(),
valuesRel.getTraitSet().plus(out));
}
|
|
Like Feedback org.apache.calcite.rel.logical.LogicalValues |
|
|
Sample 8. Code Sample / Example / Snippet of org.apache.calcite.rel.logical.LogicalCalc | |
|
public RelNode convert(RelNode rel) {
final LogicalCalc calc = (LogicalCalc) rel;
if (RexMultisetUtil.containsMultiset(calc.getProgram())) {
return null;
}
return new MongoCalcRel(
rel.getCluster(),
rel.getTraitSet().replace(out),
convert(
calc.getChild(),
calc.getTraitSet().replace(out)),
calc.getProgram(),
Project.Flags.Boxed);
}
|
|
Like Feedback org.apache.calcite.rel.logical.LogicalCalc |
|
|
Sample 9. Code Sample / Example / Snippet of org.apache.ace.log.target.store.impl.LogStoreImpl | |
|
public void testTimedWrite() throws Exception {
File storeFile = File.createTempFile("feedback", ".store");
storeFile.deleteOnExit();
final int recordCount = 10000;
final LogStoreImpl store = createLogStore();
long start = System.nanoTime();
for (int i = 0; i < recordCount; i++) {
store.put(Arrays.asList(new Event("1,2,3,4,5")));
}
long end = System.nanoTime();
System.out.printf("Writing %d records took %.3f ms.%n", recordCount, (end - start) / 1.0e6);
}
|
|
Like Feedback org.apache.ace.log.target.store.impl.LogStoreImpl |
|
|