use of org.apache.ignite.Ignite in project ignite by apache.
the class IgniteAtomicSequenceExample method main.
/**
* Executes example.
*
* @param args Command line arguments, none required.
* @throws Exception If example execution failed.
*/
public static void main(String[] args) throws Exception {
try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
System.out.println();
System.out.println(">>> Cache atomic sequence example started.");
// Try increment atomic sequence on all cluster nodes. Note that this node is also part of the cluster.
ignite.compute().broadcast(new SequenceClosure("example-sequence"));
System.out.println();
System.out.println("Finished atomic sequence example...");
System.out.println("Check all nodes for output (this node is also part of the cluster).");
System.out.println();
}
}
use of org.apache.ignite.Ignite in project ignite by apache.
the class CacheApiExample method main.
/**
* Executes example.
*
* @param args Command line arguments, none required.
* @throws IgniteException If example execution failed.
*/
public static void main(String[] args) throws IgniteException {
try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
System.out.println();
System.out.println(">>> Cache API example started.");
// Auto-close cache at the end of the example.
try (IgniteCache<Integer, String> cache = ignite.getOrCreateCache(CACHE_NAME)) {
// Demonstrate atomic map operations.
atomicMapOperations(cache);
} finally {
// Distributed cache could be removed from cluster only by #destroyCache() call.
ignite.destroyCache(CACHE_NAME);
}
}
}
use of org.apache.ignite.Ignite in project ignite by apache.
the class CacheAsyncApiExample method main.
/**
* Executes example.
*
* @param args Command line arguments, none required.
* @throws IgniteException If example execution failed.
*/
public static void main(String[] args) throws IgniteException {
try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
System.out.println();
System.out.println(">>> Cache asynchronous API example started.");
// Auto-close cache at the end of the example.
try (IgniteCache<Integer, String> cache = ignite.getOrCreateCache(CACHE_NAME)) {
Collection<IgniteFuture<?>> futs = new ArrayList<>();
// Execute several puts asynchronously.
for (int i = 0; i < 10; i++) futs.add(cache.putAsync(i, String.valueOf(i)));
// Wait for completion of all futures.
for (IgniteFuture<?> fut : futs) fut.get();
// Execute get operation asynchronously and wait for result.
cache.getAsync(1).listen(new IgniteInClosure<IgniteFuture<String>>() {
@Override
public void apply(IgniteFuture<String> fut) {
System.out.println("Get operation completed [value=" + fut.get() + ']');
}
});
} finally {
// Distributed cache could be removed from cluster only by #destroyCache() call.
ignite.destroyCache(CACHE_NAME);
}
}
}
use of org.apache.ignite.Ignite in project ignite by apache.
the class GridifySingleSplitLoadTest method testGridifyLoad.
/**
* Load test grid.
*
* @throws Exception If task execution failed.
*/
@SuppressWarnings("unchecked")
public void testGridifyLoad() throws Exception {
Ignite ignite = G.ignite(getTestIgniteInstanceName());
ignite.compute().localDeployTask(GridifyLoadTestTask.class, GridifyLoadTestTask.class.getClassLoader());
final long end = getTestDurationInMinutes() * 60 * 1000 + System.currentTimeMillis();
// Warm up.
new GridifyLoadTestJobTarget().executeLoadTestJob(3);
info("Load test will be executed for '" + getTestDurationInMinutes() + "' mins.");
info("Thread count: " + getThreadCount());
final GridLoadTestStatistics stats = new GridLoadTestStatistics();
GridTestUtils.runMultiThreaded(new Runnable() {
@Override
public void run() {
while (end - System.currentTimeMillis() > 0) {
int levels = 3;
int exp = factorial(levels);
long start = System.currentTimeMillis();
int res = new GridifyLoadTestJobTarget().executeLoadTestJob(exp);
if (res != exp)
fail("Received wrong result [expected=" + exp + ", actual=" + res + ']');
long taskCnt = stats.onTaskCompleted(null, exp, System.currentTimeMillis() - start);
if (taskCnt % 500 == 0)
info(stats.toString());
}
}
}, getThreadCount(), "grid-load-test-thread");
info("Final test statistics: " + stats);
}
use of org.apache.ignite.Ignite in project ignite by apache.
the class DistributedRegressionExample method main.
/** Run example. */
public static void main(String[] args) throws InterruptedException {
System.out.println();
System.out.println(">>> Linear regression over sparse distributed matrix API usage example started.");
// Start ignite grid.
try (Ignite ignite = Ignition.start("examples/config/example-ignite.xml")) {
System.out.println(">>> Ignite grid started.");
// Create IgniteThread, we must work with SparseDistributedMatrix inside IgniteThread
// because we create ignite cache internally.
IgniteThread igniteThread = new IgniteThread(ignite.configuration().getIgniteInstanceName(), SparseDistributedMatrixExample.class.getSimpleName(), () -> {
double[] data = { 8, 78, 284, 9.100000381, 109, 9.300000191, 68, 433, 8.699999809, 144, 7.5, 70, 739, 7.199999809, 113, 8.899999619, 96, 1792, 8.899999619, 97, 10.19999981, 74, 477, 8.300000191, 206, 8.300000191, 111, 362, 10.89999962, 124, 8.800000191, 77, 671, 10, 152, 8.800000191, 168, 636, 9.100000381, 162, 10.69999981, 82, 329, 8.699999809, 150, 11.69999981, 89, 634, 7.599999905, 134, 8.5, 149, 631, 10.80000019, 292, 8.300000191, 60, 257, 9.5, 108, 8.199999809, 96, 284, 8.800000191, 111, 7.900000095, 83, 603, 9.5, 182, 10.30000019, 130, 686, 8.699999809, 129, 7.400000095, 145, 345, 11.19999981, 158, 9.600000381, 112, 1357, 9.699999809, 186, 9.300000191, 131, 544, 9.600000381, 177, 10.60000038, 80, 205, 9.100000381, 127, 9.699999809, 130, 1264, 9.199999809, 179, 11.60000038, 140, 688, 8.300000191, 80, 8.100000381, 154, 354, 8.399999619, 103, 9.800000191, 118, 1632, 9.399999619, 101, 7.400000095, 94, 348, 9.800000191, 117, 9.399999619, 119, 370, 10.39999962, 88, 11.19999981, 153, 648, 9.899999619, 78, 9.100000381, 116, 366, 9.199999809, 102, 10.5, 97, 540, 10.30000019, 95, 11.89999962, 176, 680, 8.899999619, 80, 8.399999619, 75, 345, 9.600000381, 92, 5, 134, 525, 10.30000019, 126, 9.800000191, 161, 870, 10.39999962, 108, 9.800000191, 111, 669, 9.699999809, 77, 10.80000019, 114, 452, 9.600000381, 60, 10.10000038, 142, 430, 10.69999981, 71, 10.89999962, 238, 822, 10.30000019, 86, 9.199999809, 78, 190, 10.69999981, 93, 8.300000191, 196, 867, 9.600000381, 106, 7.300000191, 125, 969, 10.5, 162, 9.399999619, 82, 499, 7.699999809, 95, 9.399999619, 125, 925, 10.19999981, 91, 9.800000191, 129, 353, 9.899999619, 52, 3.599999905, 84, 288, 8.399999619, 110, 8.399999619, 183, 718, 10.39999962, 69, 10.80000019, 119, 540, 9.199999809, 57, 10.10000038, 180, 668, 13, 106, 9, 82, 347, 8.800000191, 40, 10, 71, 345, 9.199999809, 50, 11.30000019, 118, 463, 7.800000191, 35, 11.30000019, 121, 728, 8.199999809, 86, 12.80000019, 68, 383, 7.400000095, 57, 10, 112, 316, 10.39999962, 57, 6.699999809, 109, 388, 8.899999619, 94 };
final int nobs = 53;
final int nvars = 4;
System.out.println(">>> Create new SparseDistributedMatrix inside IgniteThread.");
// Create SparseDistributedMatrix, new cache will be created automagically.
SparseDistributedMatrix distributedMatrix = new SparseDistributedMatrix(0, 0, StorageConstants.ROW_STORAGE_MODE, StorageConstants.RANDOM_ACCESS_MODE);
System.out.println(">>> Create new linear regression object");
OLSMultipleLinearRegression regression = new OLSMultipleLinearRegression();
regression.newSampleData(data, nobs, nvars, distributedMatrix);
System.out.println();
System.out.println(">>> Estimates the regression parameters b:");
System.out.println(Arrays.toString(regression.estimateRegressionParameters()));
System.out.println(">>> Estimates the residuals, ie u = y - X*b:");
System.out.println(Arrays.toString(regression.estimateResiduals()));
System.out.println(">>> Standard errors of the regression parameters:");
System.out.println(Arrays.toString(regression.estimateRegressionParametersStandardErrors()));
System.out.println(">>> Estimates the variance of the regression parameters, ie Var(b):");
Tracer.showAscii(regression.estimateRegressionParametersVariance());
System.out.println(">>> Estimates the standard error of the regression:");
System.out.println(regression.estimateRegressionStandardError());
System.out.println(">>> R-Squared statistic:");
System.out.println(regression.calculateRSquared());
System.out.println(">>> Adjusted R-squared statistic:");
System.out.println(regression.calculateAdjustedRSquared());
System.out.println(">>> Returns the variance of the regressand, ie Var(y):");
System.out.println(regression.estimateErrorVariance());
});
igniteThread.start();
igniteThread.join();
}
}
Aggregations