@Test
public void testCrossValidationOneSchema() throws TupleMRException, IOException {
Configuration conf = getConf();
int maxIndex = SCHEMA.getFields().size() - 1;
for (int randomSchema = 0; randomSchema < MAX_RANDOM_SCHEMAS; randomSchema++) {
Schema schema = permuteSchema(SCHEMA);
OrderBy sortCriteria = createRandomSortCriteria(schema, maxIndex + 1);
// TODO could we get empty group fields ??
String[] groupFields =
getFirstFields(sortCriteria, 1 + random.nextInt(sortCriteria.getElements().size() - 1));
ITuple[] tuples = new ITuple[] {new Tuple(schema), new Tuple(schema)};
for (ITuple tuple : tuples) {
fillTuple(false, tuple, 0, maxIndex);
}
for (int minIndex = maxIndex; minIndex >= 0; minIndex--) {
/* trick for speeding up the tests */
DCUtils.cleanupTemporaryInstanceCache(conf, "comparator.dat");
TupleMRConfigBuilder builder = new TupleMRConfigBuilder();
builder.addIntermediateSchema(schema);
builder.setGroupByFields(groupFields);
builder.setOrderBy(sortCriteria);
TupleMRConfig tupleMRConf = builder.buildConf();
TupleMRConfig.set(tupleMRConf, conf);
// tupleMRConf has changed -> we need a new Serialization object
ser = new HadoopSerialization(conf);
SortComparator sortComparator = new SortComparator();
GroupComparator groupComparator = new GroupComparator();
sortComparator.setConf(conf);
groupComparator.setConf(conf);
for (ITuple tuple : tuples) {
fillTuple(true, tuple, minIndex, maxIndex);
}
for (int indexTuple1 = 0; indexTuple1 < tuples.length; indexTuple1++) {
for (int indexTuple2 = indexTuple1 + 1; indexTuple2 < tuples.length; indexTuple2++) {
ITuple tuple1 = tuples[indexTuple1];
ITuple tuple2 = tuples[indexTuple2];
assertSameComparison("Sort comparator", sortComparator, tuple1, tuple2);
assertOppositeOrEqualsComparison(sortComparator, tuple1, tuple2);
assertSameComparison("Group comparator", groupComparator, tuple1, tuple2);
assertOppositeOrEqualsComparison(groupComparator, tuple1, tuple2);
}
}
}
}
}
protected static String[] getFirstFields(OrderBy sortCriteria, int numFields) {
String[] result = new String[numFields];
for (int i = 0; i < numFields; i++) {
SortElement element = sortCriteria.getElements().get(i);
result[i] = element.getName();
}
return result;
}
@Override
public int run(String[] args) throws Exception {
// Validate params etc
JCommander jComm = new JCommander(this);
jComm.setProgramName("Splout Page Counts example");
try {
jComm.parse(args);
} catch (ParameterException e) {
System.err.println(e.getMessage());
jComm.usage();
System.exit(-1);
}
boolean generate = !noGenerate; // just for clarifying
if (generateTupleFiles && deploy) {
System.err.println("Can't run a 'dry' TupleFile generation and deploy it.");
jComm.usage();
System.exit(-1);
}
Path outPath = new Path(outputPath);
FileSystem outFs = outPath.getFileSystem(getConf());
if (!FileSystem.getLocal(conf).equals(FileSystem.get(conf))) {
File nativeLibs = new File("native");
if (nativeLibs.exists()) {
SploutHadoopConfiguration.addSQLite4JavaNativeLibsToDC(conf);
}
}
if (generate) {
Path inputPath = new Path(this.inputPath);
FileSystem inputFileSystem = inputPath.getFileSystem(conf);
FileStatus[] fileStatuses = inputFileSystem.listStatus(inputPath);
// define the schema that the resultant table will have: date, hour, pagename, pageviews
final Schema tableSchema =
new Schema(
"pagecounts",
Fields.parse("date:string, hour:string, pagename:string, pageviews:int"));
// define the schema of the input files: projectcode, pagename, pageviews, bytes
Schema fileSchema =
new Schema(
"pagecountsfile",
Fields.parse("projectcode:string, pagename:string, pageviews:int, bytes:long"));
// instantiate a TableBuilder
TableBuilder tableBuilder = new TableBuilder(tableSchema);
// for every input file...
for (FileStatus fileStatus : fileStatuses) {
String fileName = fileStatus.getPath().getName().toString();
// strip the date and the hour from the file name
String fileDate = fileName.split("-")[1];
String fileHour = fileName.split("-")[2].substring(0, 2);
// instantiate a custom RecordProcessor to process the records of this file
PageCountsRecordProcessor recordProcessor =
new PageCountsRecordProcessor(tableSchema, fileDate, fileHour);
// use the tableBuilder method for adding each of the files to the mix
tableBuilder.addCSVTextFile(
fileStatus.getPath(),
' ',
TupleTextInputFormat.NO_QUOTE_CHARACTER,
TupleTextInputFormat.NO_ESCAPE_CHARACTER,
false,
false,
TupleTextInputFormat.NO_NULL_STRING,
fileSchema,
recordProcessor);
}
// partition the dataset by pagename - which should give a fair even distribution.
tableBuilder.partitionBy("pagename");
// create a compound index on pagename, date so that typical queries for the dataset will be
// fast
tableBuilder.createIndex("pagename", "date");
long nonExactPageSize = memoryForIndexing / 32000; // number of pages
int pageSize = (int) Math.pow(2, (int) Math.round(Math.log(nonExactPageSize) / Math.log(2)));
Log.info(
"Pagesize = "
+ pageSize
+ " as memory for indexing was ["
+ memoryForIndexing
+ "] and there are 32000 pages.");
tableBuilder.initialSQL("pragma page_size=" + pageSize);
// insertion order is very important for optimizing query speed because it makes data be
// co-located in disk
tableBuilder.insertionSortOrder(OrderBy.parse("pagename:asc, date:asc"));
// instantiate a TablespaceBuilder
TablespaceBuilder tablespaceBuilder = new TablespaceBuilder();
// we will partition this dataset in as many partitions as:
tablespaceBuilder.setNPartitions(nPartitions);
tablespaceBuilder.add(tableBuilder.build());
// we turn a specific SQLite pragma on for making autocomplete queries fast
tablespaceBuilder.initStatements("pragma case_sensitive_like=true;");
HadoopUtils.deleteIfExists(outFs, outPath);
// finally, instantiate a TablespaceGenerator and execute it
TablespaceGenerator tablespaceViewBuilder;
if (generateTupleFiles) {
// we subclass TablespaceGenerator to be able to run the generation without outputting the
// SQLite stores, for
// benchmark comparisons.
// In the future this feature may be useful in general for debugging store creation.
tablespaceViewBuilder =
new TablespaceGenerator(tablespaceBuilder.build(), outPath) {
@Override
public void generateView(
Configuration conf, SamplingType samplingType, SamplingOptions samplingOptions)
throws Exception {
prepareOutput(conf);
final int nPartitions = tablespace.getnPartitions();
if (nPartitions > 1) {
partitionMap = sample(nPartitions, conf, samplingType, samplingOptions);
} else {
partitionMap = PartitionMap.oneShardOpenedMap();
}
writeOutputMetadata(conf);
TupleMRBuilder builder = createMRBuilder(nPartitions, conf);
// Set a TupleOutput here instead of SQLiteOutput
builder.setOutput(
new Path(outputPath, OUT_STORE),
new TupleOutputFormat(tableSchema),
ITuple.class,
NullWritable.class);
Job job = builder.createJob();
executeViewGeneration(job);
}
};
} else {
// ... otherwise a standard TablespaceGenerator is used.
tablespaceViewBuilder = new TablespaceGenerator(tablespaceBuilder.build(), outPath);
}
tablespaceViewBuilder.generateView(
getConf(), SamplingType.RESERVOIR, new TupleSampler.DefaultSamplingOptions());
}
if (deploy) {
// use StoreDeployerTool for deploying the already generated dataset
StoreDeployerTool deployer = new StoreDeployerTool(qnode, getConf());
ArrayList<TablespaceDepSpec> deployments = new ArrayList<TablespaceDepSpec>();
deployments.add(new TablespaceDepSpec("pagecounts", outPath.toString(), repFactor, null));
deployer.deploy(deployments);
}
return 1;
}
