use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo in project hive by apache.
the class GenericUDFJsonRead method initialize.
@Override
public ObjectInspector initialize(ObjectInspector[] arguments) throws UDFArgumentException {
checkArgsSize(arguments, 2, 2);
checkArgPrimitive(arguments, 0);
checkArgPrimitive(arguments, 1);
if (!ObjectInspectorUtils.isConstantObjectInspector(arguments[1])) {
throw new UDFArgumentTypeException(1, getFuncName() + " argument 2 may only be a constant");
}
inputConverter = new TextConverter((PrimitiveObjectInspector) arguments[0]);
String typeStr = getConstantStringValue(arguments, 1);
try {
final TypeInfo t = TypeInfoUtils.getTypeInfoFromTypeString(typeStr);
final ObjectInspector oi = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(t);
jsonReader = new HiveJsonReader(oi);
jsonReader.enable(Feature.PRIMITIVE_TO_WRITABLE);
} catch (Exception e) {
throw new UDFArgumentException(getFuncName() + ": Error parsing typestring: " + e.getMessage());
}
return jsonReader.getObjectInspector();
}
use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo in project hive by apache.
the class TestVectorDateDiff method doRowDateAddSubTest.
private void doRowDateAddSubTest(TypeInfo dateTimeStringTypeInfo1, TypeInfo dateTimeStringTypeInfo2, List<String> columns, List<ExprNodeDesc> children, ExprNodeGenericFuncDesc exprDesc, Object[][] randomRows, ColumnScalarMode columnScalarMode, ObjectInspector rowInspector, Object[] resultObjects) throws Exception {
/*
System.out.println(
"*DEBUG* dateTimeStringTypeInfo " + dateTimeStringTypeInfo1.toString() +
" dateTimeStringTypeInfo2 " + dateTimeStringTypeInfo2 +
" dateDiffTestMode ROW_MODE" +
" columnScalarMode " + columnScalarMode +
" exprDesc " + exprDesc.toString());
*/
HiveConf hiveConf = new HiveConf();
ExprNodeEvaluator evaluator = ExprNodeEvaluatorFactory.get(exprDesc, hiveConf);
evaluator.initialize(rowInspector);
ObjectInspector objectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(TypeInfoFactory.intTypeInfo);
final int rowCount = randomRows.length;
for (int i = 0; i < rowCount; i++) {
Object[] row = randomRows[i];
Object result = evaluator.evaluate(row);
Object copyResult = ObjectInspectorUtils.copyToStandardObject(result, objectInspector, ObjectInspectorCopyOption.WRITABLE);
resultObjects[i] = copyResult;
}
}
use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo in project hive by apache.
the class TestVectorNull method doIsNullOnRandomDataType.
private boolean doIsNullOnRandomDataType(Random random, String functionName, boolean isFilter) throws Exception {
String typeName;
if (functionName.equals("not")) {
typeName = "boolean";
} else {
typeName = VectorRandomRowSource.getRandomTypeName(random, SupportedTypes.ALL, /* allowedTypeNameSet */
null);
typeName = VectorRandomRowSource.getDecoratedTypeName(random, typeName, SupportedTypes.ALL, /* allowedTypeNameSet */
null, /* depth */
0, /* maxDepth */
2);
}
TypeInfo typeInfo = TypeInfoUtils.getTypeInfoFromTypeString(typeName);
// ----------------------------------------------------------------------------------------------
ObjectInspector objectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(typeInfo);
// ----------------------------------------------------------------------------------------------
GenerationSpec generationSpec = GenerationSpec.createSameType(typeInfo);
List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
generationSpecList.add(generationSpec);
explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
VectorRandomRowSource rowSource = new VectorRandomRowSource();
rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
0, /* allowNull */
true, /* isUnicodeOk */
true, explicitDataTypePhysicalVariationList);
List<String> columns = new ArrayList<String>();
columns.add("col1");
ExprNodeColumnDesc col1Expr = new ExprNodeColumnDesc(typeInfo, "col1", "table", false);
List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
children.add(col1Expr);
String[] columnNames = columns.toArray(new String[0]);
Object[][] randomRows = rowSource.randomRows(100000);
VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
final GenericUDF udf;
final ObjectInspector outputObjectInspector;
switch(functionName) {
case "isnull":
udf = new GenericUDFOPNull();
break;
case "isnotnull":
udf = new GenericUDFOPNotNull();
break;
case "not":
udf = new GenericUDFOPNot();
break;
default:
throw new RuntimeException("Unexpected function name " + functionName);
}
ObjectInspector[] argumentOIs = new ObjectInspector[] { objectInspector };
outputObjectInspector = udf.initialize(argumentOIs);
TypeInfo outputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(outputObjectInspector);
ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(TypeInfoFactory.booleanTypeInfo, udf, children);
final int rowCount = randomRows.length;
Object[][] resultObjectsArray = new Object[NullTestMode.count][];
for (int i = 0; i < NullTestMode.count; i++) {
Object[] resultObjects = new Object[rowCount];
resultObjectsArray[i] = resultObjects;
NullTestMode nullTestMode = NullTestMode.values()[i];
switch(nullTestMode) {
case ROW_MODE:
if (!doRowCastTest(typeInfo, isFilter, columns, children, udf, exprDesc, randomRows, rowSource.rowStructObjectInspector(), resultObjects)) {
return false;
}
break;
case ADAPTOR:
case VECTOR_EXPRESSION:
if (!doVectorCastTest(typeInfo, isFilter, columns, columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), children, udf, exprDesc, nullTestMode, batchSource, exprDesc.getWritableObjectInspector(), outputTypeInfo, resultObjects)) {
return false;
}
break;
default:
throw new RuntimeException("Unexpected IF statement test mode " + nullTestMode);
}
}
for (int i = 0; i < rowCount; i++) {
// Row-mode is the expected value.
Object expectedResult = resultObjectsArray[0][i];
for (int v = 1; v < NullTestMode.count; v++) {
Object vectorResult = resultObjectsArray[v][i];
NullTestMode nullTestMode = NullTestMode.values()[v];
if (isFilter && expectedResult == null && vectorResult != null) {
// This is OK.
boolean vectorBoolean = ((BooleanWritable) vectorResult).get();
if (vectorBoolean) {
Assert.fail("Row " + i + " typeName " + typeName + " outputTypeName " + outputTypeInfo.getTypeName() + " isFilter " + isFilter + " " + nullTestMode + " result is NOT NULL and true" + " does not match row-mode expected result is NULL which means false here" + " row values " + Arrays.toString(randomRows[i]) + " exprDesc " + exprDesc.toString());
}
} else if (expectedResult == null || vectorResult == null) {
if (expectedResult != null || vectorResult != null) {
Assert.fail("Row " + i + " sourceTypeName " + typeName + " isFilter " + isFilter + " " + nullTestMode + " result is NULL " + (vectorResult == null ? "YES" : "NO result " + vectorResult.toString()) + " does not match row-mode expected result is NULL " + (expectedResult == null ? "YES" : "NO result " + expectedResult.toString()) + " row values " + Arrays.toString(randomRows[i]) + " exprDesc " + exprDesc.toString());
}
} else {
if (!expectedResult.equals(vectorResult)) {
Assert.fail("Row " + i + " sourceTypeName " + typeName + " isFilter " + isFilter + " " + nullTestMode + " result " + vectorResult.toString() + " (" + vectorResult.getClass().getSimpleName() + ")" + " does not match row-mode expected result " + expectedResult.toString() + " (" + expectedResult.getClass().getSimpleName() + ")" + " row values " + Arrays.toString(randomRows[i]) + " exprDesc " + exprDesc.toString());
}
}
}
}
return true;
}
use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo in project hive by apache.
the class TestVectorTimestampExtract method doRowCastTest.
private boolean doRowCastTest(TypeInfo dateTimeStringTypeInfo, List<String> columns, List<ExprNodeDesc> children, ExprNodeGenericFuncDesc exprDesc, Object[][] randomRows, ObjectInspector rowInspector, Object[] resultObjects) throws Exception {
/*
System.out.println(
"*DEBUG* dateTimeStringTypeInfo " + dateTimeStringTypeInfo.toString() +
" timestampExtractTestMode ROW_MODE" +
" exprDesc " + exprDesc.toString());
*/
HiveConf hiveConf = new HiveConf();
ExprNodeEvaluator evaluator = ExprNodeEvaluatorFactory.get(exprDesc, hiveConf);
try {
evaluator.initialize(rowInspector);
} catch (HiveException e) {
return false;
}
ObjectInspector objectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(TypeInfoFactory.intTypeInfo);
PrimitiveCategory dateTimeStringPrimitiveCategory = ((PrimitiveTypeInfo) dateTimeStringTypeInfo).getPrimitiveCategory();
final int rowCount = randomRows.length;
for (int i = 0; i < rowCount; i++) {
Object[] row = randomRows[i];
Object object = row[0];
Object result;
switch(dateTimeStringPrimitiveCategory) {
case TIMESTAMP:
result = evaluator.evaluate((TimestampWritableV2) object);
break;
case DATE:
result = evaluator.evaluate((DateWritableV2) object);
break;
case STRING:
{
Text text;
if (object == null) {
text = null;
} else if (object instanceof String) {
text = new Text();
text.set((String) object);
} else {
text = (Text) object;
}
result = evaluator.evaluate(text);
}
break;
default:
throw new RuntimeException("Unexpected date timestamp string primitive category " + dateTimeStringPrimitiveCategory);
}
Object copyResult = ObjectInspectorUtils.copyToStandardObject(result, objectInspector, ObjectInspectorCopyOption.WRITABLE);
resultObjects[i] = copyResult;
}
return true;
}
use of org.apache.hadoop.hive.serde2.typeinfo.TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo in project hive by apache.
the class TestVectorIndex method doIndexOnRandomDataType.
private boolean doIndexOnRandomDataType(Random random, boolean isList, String keyTypeName, String elementRootTypeName, boolean allowNulls, boolean isScalarIndex) throws Exception {
String elementTypeName = VectorRandomRowSource.getDecoratedTypeName(random, elementRootTypeName, SupportedTypes.ALL, /* allowedTypeNameSet */
null, /* depth */
0, /* maxDepth */
3);
TypeInfo elementTypeInfo = TypeInfoUtils.getTypeInfoFromTypeString(elementTypeName);
ObjectInspector elementObjectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(elementTypeInfo);
// ----------------------------------------------------------------------------------------------
final TypeInfo keyTypeInfo;
if (isList) {
keyTypeInfo = TypeInfoFactory.intTypeInfo;
} else {
keyTypeInfo = TypeInfoUtils.getTypeInfoFromTypeString(keyTypeName);
}
final ObjectInspector keyObjectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(keyTypeInfo);
Object exampleObject = (isList ? ((WritableIntObjectInspector) keyObjectInspector).create(0) : VectorRandomRowSource.randomWritable(random, keyTypeInfo, keyObjectInspector, DataTypePhysicalVariation.NONE, /* allowNull */
false));
WritableComparator writableComparator = WritableComparator.get((Class<? extends WritableComparable>) exampleObject.getClass());
final int allKeyCount = 10 + random.nextInt(10);
final int keyCount = 5 + random.nextInt(allKeyCount / 2);
List<Object> allKeyList = new ArrayList<Object>(allKeyCount);
Set<Object> allKeyTreeSet = new TreeSet<Object>(writableComparator);
int fillAllKeyCount = 0;
while (fillAllKeyCount < allKeyCount) {
Object object;
if (isList) {
WritableIntObjectInspector writableOI = (WritableIntObjectInspector) keyObjectInspector;
int index = random.nextInt(keyCount);
object = writableOI.create(index);
while (allKeyTreeSet.contains(object)) {
index = (random.nextBoolean() ? random.nextInt() : (random.nextBoolean() ? -1 : keyCount));
object = writableOI.create(index);
}
} else {
do {
object = VectorRandomRowSource.randomWritable(random, keyTypeInfo, keyObjectInspector, DataTypePhysicalVariation.NONE, /* allowNull */
false);
} while (allKeyTreeSet.contains(object));
}
allKeyList.add(object);
allKeyTreeSet.add(object);
fillAllKeyCount++;
}
List<Object> keyList = new ArrayList<Object>();
Set<Object> keyTreeSet = new TreeSet<Object>(writableComparator);
int fillKeyCount = 0;
while (fillKeyCount < keyCount) {
Object newKey = allKeyList.get(random.nextInt(allKeyCount));
if (keyTreeSet.contains(newKey)) {
continue;
}
keyList.add(newKey);
keyTreeSet.add(newKey);
fillKeyCount++;
}
// ----------------------------------------------------------------------------------------------
final TypeInfo typeInfo;
if (isList) {
ListTypeInfo listTypeInfo = new ListTypeInfo();
listTypeInfo.setListElementTypeInfo(elementTypeInfo);
typeInfo = listTypeInfo;
} else {
MapTypeInfo mapTypeInfo = new MapTypeInfo();
mapTypeInfo.setMapKeyTypeInfo(keyTypeInfo);
mapTypeInfo.setMapValueTypeInfo(elementTypeInfo);
typeInfo = mapTypeInfo;
}
final String typeName = typeInfo.getTypeName();
final ObjectInspector objectInspector = TypeInfoUtils.getStandardWritableObjectInspectorFromTypeInfo(typeInfo);
// ----------------------------------------------------------------------------------------------
GenerationSpec generationSpec = GenerationSpec.createSameType(typeInfo);
List<GenerationSpec> generationSpecList = new ArrayList<GenerationSpec>();
List<DataTypePhysicalVariation> explicitDataTypePhysicalVariationList = new ArrayList<DataTypePhysicalVariation>();
List<String> columns = new ArrayList<String>();
List<ExprNodeDesc> children = new ArrayList<ExprNodeDesc>();
int columnNum = 1;
ExprNodeDesc keyColExpr;
if (!isScalarIndex) {
generationSpecList.add(GenerationSpec.createValueList(keyTypeInfo, keyList));
explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
String columnName = "col" + columnNum++;
columns.add(columnName);
keyColExpr = new ExprNodeColumnDesc(keyTypeInfo, columnName, "table", false);
} else {
Object scalarWritable = keyList.get(random.nextInt(keyCount));
final Object scalarObject = VectorRandomRowSource.getNonWritableObject(scalarWritable, keyTypeInfo, keyObjectInspector);
keyColExpr = new ExprNodeConstantDesc(keyTypeInfo, scalarObject);
}
/*
System.out.println("*DEBUG* typeName " + typeName);
System.out.println("*DEBUG* keyColExpr " + keyColExpr.toString());
System.out.println("*DEBUG* keyList " + keyList.toString());
System.out.println("*DEBUG* allKeyList " + allKeyList.toString());
*/
generationSpecList.add(GenerationSpec.createValueList(typeInfo, keyList));
explicitDataTypePhysicalVariationList.add(DataTypePhysicalVariation.NONE);
String columnName = "col" + columnNum++;
columns.add(columnName);
ExprNodeDesc listOrMapColExpr;
listOrMapColExpr = new ExprNodeColumnDesc(typeInfo, columnName, "table", false);
children.add(listOrMapColExpr);
children.add(keyColExpr);
VectorRandomRowSource rowSource = new VectorRandomRowSource();
rowSource.initGenerationSpecSchema(random, generationSpecList, /* maxComplexDepth */
0, /* allowNull */
allowNulls, /* isUnicodeOk */
true, explicitDataTypePhysicalVariationList);
String[] columnNames = columns.toArray(new String[0]);
Object[][] randomRows = rowSource.randomRows(100000);
VectorRandomBatchSource batchSource = VectorRandomBatchSource.createInterestingBatches(random, rowSource, randomRows, null);
final GenericUDF udf = new GenericUDFIndex();
ObjectInspector[] argumentOIs = new ObjectInspector[2];
argumentOIs[0] = objectInspector;
argumentOIs[1] = keyObjectInspector;
final ObjectInspector outputObjectInspector = udf.initialize(argumentOIs);
TypeInfo outputTypeInfo = TypeInfoUtils.getTypeInfoFromObjectInspector(outputObjectInspector);
ExprNodeGenericFuncDesc exprDesc = new ExprNodeGenericFuncDesc(elementTypeInfo, udf, children);
System.out.println("here");
final int rowCount = randomRows.length;
Object[][] resultObjectsArray = new Object[IndexTestMode.count][];
for (int i = 0; i < IndexTestMode.count; i++) {
Object[] resultObjects = new Object[rowCount];
resultObjectsArray[i] = resultObjects;
IndexTestMode indexTestMode = IndexTestMode.values()[i];
switch(indexTestMode) {
case ROW_MODE:
if (!doRowCastTest(typeInfo, columns, children, udf, exprDesc, randomRows, rowSource.rowStructObjectInspector(), elementObjectInspector, outputTypeInfo, resultObjects)) {
return false;
}
break;
case ADAPTOR:
case VECTOR_EXPRESSION:
if (!doVectorCastTest(typeInfo, columns, columnNames, rowSource.typeInfos(), rowSource.dataTypePhysicalVariations(), children, udf, exprDesc, indexTestMode, batchSource, exprDesc.getWritableObjectInspector(), outputTypeInfo, resultObjects)) {
return false;
}
break;
default:
throw new RuntimeException("Unexpected IF statement test mode " + indexTestMode);
}
}
for (int i = 0; i < rowCount; i++) {
// Row-mode is the expected value.
Object expectedResult = resultObjectsArray[0][i];
for (int v = 1; v < IndexTestMode.count; v++) {
Object vectorResult = resultObjectsArray[v][i];
IndexTestMode indexTestMode = IndexTestMode.values()[v];
if (expectedResult == null || vectorResult == null) {
if (expectedResult != null || vectorResult != null) {
Assert.fail("Row " + i + " sourceTypeName " + typeName + " " + indexTestMode + " result is NULL " + (vectorResult == null ? "YES" : "NO result " + vectorResult.toString()) + " does not match row-mode expected result is NULL " + (expectedResult == null ? "YES" : "NO result " + expectedResult.toString()) + " row values " + Arrays.toString(randomRows[i]) + " exprDesc " + exprDesc.toString());
}
} else {
if (!expectedResult.equals(vectorResult)) {
Assert.fail("Row " + i + " sourceTypeName " + typeName + " " + indexTestMode + " result " + vectorResult.toString() + " (" + vectorResult.getClass().getSimpleName() + ")" + " does not match row-mode expected result " + expectedResult.toString() + " (" + expectedResult.getClass().getSimpleName() + ")" + " row values " + Arrays.toString(randomRows[i]) + " exprDesc " + exprDesc.toString());
}
}
}
}
return true;
}
Aggregations