use of org.apache.flink.table.data.columnar.vector.heap.HeapTimestampVector in project flink by apache.
the class ParquetSplitReaderUtil method createVectorFromConstant.
public static ColumnVector createVectorFromConstant(LogicalType type, Object value, int batchSize) {
switch(type.getTypeRoot()) {
case CHAR:
case VARCHAR:
case BINARY:
case VARBINARY:
HeapBytesVector bsv = new HeapBytesVector(batchSize);
if (value == null) {
bsv.fillWithNulls();
} else {
bsv.fill(value instanceof byte[] ? (byte[]) value : value.toString().getBytes(StandardCharsets.UTF_8));
}
return bsv;
case BOOLEAN:
HeapBooleanVector bv = new HeapBooleanVector(batchSize);
if (value == null) {
bv.fillWithNulls();
} else {
bv.fill((boolean) value);
}
return bv;
case TINYINT:
HeapByteVector byteVector = new HeapByteVector(batchSize);
if (value == null) {
byteVector.fillWithNulls();
} else {
byteVector.fill(((Number) value).byteValue());
}
return byteVector;
case SMALLINT:
HeapShortVector sv = new HeapShortVector(batchSize);
if (value == null) {
sv.fillWithNulls();
} else {
sv.fill(((Number) value).shortValue());
}
return sv;
case INTEGER:
HeapIntVector iv = new HeapIntVector(batchSize);
if (value == null) {
iv.fillWithNulls();
} else {
iv.fill(((Number) value).intValue());
}
return iv;
case BIGINT:
HeapLongVector lv = new HeapLongVector(batchSize);
if (value == null) {
lv.fillWithNulls();
} else {
lv.fill(((Number) value).longValue());
}
return lv;
case DECIMAL:
DecimalType decimalType = (DecimalType) type;
int precision = decimalType.getPrecision();
int scale = decimalType.getScale();
DecimalData decimal = value == null ? null : Preconditions.checkNotNull(DecimalData.fromBigDecimal((BigDecimal) value, precision, scale));
ColumnVector internalVector;
if (ParquetSchemaConverter.is32BitDecimal(precision)) {
internalVector = createVectorFromConstant(new IntType(), decimal == null ? null : (int) decimal.toUnscaledLong(), batchSize);
} else if (ParquetSchemaConverter.is64BitDecimal(precision)) {
internalVector = createVectorFromConstant(new BigIntType(), decimal == null ? null : decimal.toUnscaledLong(), batchSize);
} else {
internalVector = createVectorFromConstant(new VarBinaryType(), decimal == null ? null : decimal.toUnscaledBytes(), batchSize);
}
return new ParquetDecimalVector(internalVector);
case FLOAT:
HeapFloatVector fv = new HeapFloatVector(batchSize);
if (value == null) {
fv.fillWithNulls();
} else {
fv.fill(((Number) value).floatValue());
}
return fv;
case DOUBLE:
HeapDoubleVector dv = new HeapDoubleVector(batchSize);
if (value == null) {
dv.fillWithNulls();
} else {
dv.fill(((Number) value).doubleValue());
}
return dv;
case DATE:
if (value instanceof LocalDate) {
value = Date.valueOf((LocalDate) value);
}
return createVectorFromConstant(new IntType(), value == null ? null : toInternal((Date) value), batchSize);
case TIMESTAMP_WITHOUT_TIME_ZONE:
HeapTimestampVector tv = new HeapTimestampVector(batchSize);
if (value == null) {
tv.fillWithNulls();
} else {
tv.fill(TimestampData.fromLocalDateTime((LocalDateTime) value));
}
return tv;
default:
throw new UnsupportedOperationException("Unsupported type: " + type);
}
}
use of org.apache.flink.table.data.columnar.vector.heap.HeapTimestampVector in project flink by apache.
the class ColumnVectorTest method testTimestamp.
@Test
public void testTimestamp() {
HeapTimestampVector vector = new HeapTimestampVector(SIZE);
for (int i = 0; i < SIZE; i++) {
vector.setTimestamp(i, TimestampData.fromEpochMillis(i, i));
}
for (int i = 0; i < SIZE; i++) {
assertEquals(TimestampData.fromEpochMillis(i, i), vector.getTimestamp(i, 9));
}
vector.fill(TimestampData.fromEpochMillis(22, 22));
for (int i = 0; i < SIZE; i++) {
assertEquals(TimestampData.fromEpochMillis(22, 22), vector.getTimestamp(i, 9));
}
vector.setDictionary(new TestDictionary(IntStream.range(0, SIZE).mapToObj(i -> TimestampData.fromEpochMillis(i, i)).toArray()));
setRangeDictIds(vector);
for (int i = 0; i < SIZE; i++) {
assertEquals(TimestampData.fromEpochMillis(i, i), vector.getTimestamp(i, 9));
}
}
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