private void readFixedLenByteArrayBatch(int rowId, int num, ColumnVector column, int arrayLen)
throws IOException {
VectorizedValuesReader data = (VectorizedValuesReader) dataColumn;
// This is where we implement support for the valid type conversions.
// TODO: implement remaining type conversions
if (DecimalType.is32BitDecimalType(column.dataType())) {
for (int i = 0; i < num; i++) {
if (defColumn.readInteger() == maxDefLevel) {
column.putInt(
rowId + i, (int) ParquetRowConverter.binaryToUnscaledLong(data.readBinary(arrayLen)));
} else {
column.putNull(rowId + i);
}
}
} else if (DecimalType.is64BitDecimalType(column.dataType())) {
for (int i = 0; i < num; i++) {
if (defColumn.readInteger() == maxDefLevel) {
column.putLong(
rowId + i, ParquetRowConverter.binaryToUnscaledLong(data.readBinary(arrayLen)));
} else {
column.putNull(rowId + i);
}
}
} else if (DecimalType.isByteArrayDecimalType(column.dataType())) {
for (int i = 0; i < num; i++) {
if (defColumn.readInteger() == maxDefLevel) {
column.putByteArray(rowId + i, data.readBinary(arrayLen).getBytes());
} else {
column.putNull(rowId + i);
}
}
} else {
throw new UnsupportedOperationException("Unimplemented type: " + column.dataType());
}
}
private void readFloatBatch(int rowId, int num, ColumnVector column) throws IOException {
// This is where we implement support for the valid type conversions.
// TODO: support implicit cast to double?
if (column.dataType() == DataTypes.FloatType) {
defColumn.readFloats(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else {
throw new UnsupportedOperationException("Unsupported conversion to: " + column.dataType());
}
}
private void readDoubleBatch(int rowId, int num, ColumnVector column) throws IOException {
// This is where we implement support for the valid type conversions.
// TODO: implement remaining type conversions
if (column.dataType() == DataTypes.DoubleType) {
defColumn.readDoubles(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else {
throw new UnsupportedOperationException("Unimplemented type: " + column.dataType());
}
}
private void readLongBatch(int rowId, int num, ColumnVector column) throws IOException {
// This is where we implement support for the valid type conversions.
if (column.dataType() == DataTypes.LongType
|| DecimalType.is64BitDecimalType(column.dataType())) {
defColumn.readLongs(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else {
throw new UnsupportedOperationException("Unsupported conversion to: " + column.dataType());
}
}
private void readBinaryBatch(int rowId, int num, ColumnVector column) throws IOException {
// This is where we implement support for the valid type conversions.
// TODO: implement remaining type conversions
VectorizedValuesReader data = (VectorizedValuesReader) dataColumn;
if (column.isArray()) {
defColumn.readBinarys(num, column, rowId, maxDefLevel, data);
} else if (column.dataType() == DataTypes.TimestampType) {
for (int i = 0; i < num; i++) {
if (defColumn.readInteger() == maxDefLevel) {
column.putLong(
rowId + i,
// Read 12 bytes for INT96
ParquetRowConverter.binaryToSQLTimestamp(data.readBinary(12)));
} else {
column.putNull(rowId + i);
}
}
} else {
throw new UnsupportedOperationException("Unimplemented type: " + column.dataType());
}
}
private void readIntBatch(int rowId, int num, ColumnVector column) throws IOException {
// This is where we implement support for the valid type conversions.
// TODO: implement remaining type conversions
if (column.dataType() == DataTypes.IntegerType
|| column.dataType() == DataTypes.DateType
|| DecimalType.is32BitDecimalType(column.dataType())) {
defColumn.readIntegers(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else if (column.dataType() == DataTypes.ByteType) {
defColumn.readBytes(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else if (column.dataType() == DataTypes.ShortType) {
defColumn.readShorts(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
} else {
throw new UnsupportedOperationException("Unimplemented type: " + column.dataType());
}
}
/**
* For all the read*Batch functions, reads `num` values from this columnReader into column. It is
* guaranteed that num is smaller than the number of values left in the current page.
*/
private void readBooleanBatch(int rowId, int num, ColumnVector column) throws IOException {
assert (column.dataType() == DataTypes.BooleanType);
defColumn.readBooleans(num, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
}
/** Reads `num` values into column, decoding the values from `dictionaryIds` and `dictionary`. */
private void decodeDictionaryIds(
int rowId, int num, ColumnVector column, ColumnVector dictionaryIds) {
switch (descriptor.getType()) {
case INT32:
if (column.dataType() == DataTypes.IntegerType
|| DecimalType.is32BitDecimalType(column.dataType())) {
for (int i = rowId; i < rowId + num; ++i) {
column.putInt(i, dictionary.decodeToInt(dictionaryIds.getInt(i)));
}
} else if (column.dataType() == DataTypes.ByteType) {
for (int i = rowId; i < rowId + num; ++i) {
column.putByte(i, (byte) dictionary.decodeToInt(dictionaryIds.getInt(i)));
}
} else if (column.dataType() == DataTypes.ShortType) {
for (int i = rowId; i < rowId + num; ++i) {
column.putShort(i, (short) dictionary.decodeToInt(dictionaryIds.getInt(i)));
}
} else {
throw new UnsupportedOperationException("Unimplemented type: " + column.dataType());
}
break;
case INT64:
if (column.dataType() == DataTypes.LongType
|| DecimalType.is64BitDecimalType(column.dataType())) {
for (int i = rowId; i < rowId + num; ++i) {
column.putLong(i, dictionary.decodeToLong(dictionaryIds.getInt(i)));
}
} else {
throw new UnsupportedOperationException("Unimplemented type: " + column.dataType());
}
break;
case FLOAT:
for (int i = rowId; i < rowId + num; ++i) {
column.putFloat(i, dictionary.decodeToFloat(dictionaryIds.getInt(i)));
}
break;
case DOUBLE:
for (int i = rowId; i < rowId + num; ++i) {
column.putDouble(i, dictionary.decodeToDouble(dictionaryIds.getInt(i)));
}
break;
case INT96:
if (column.dataType() == DataTypes.TimestampType) {
for (int i = rowId; i < rowId + num; ++i) {
// TODO: Convert dictionary of Binaries to dictionary of Longs
Binary v = dictionary.decodeToBinary(dictionaryIds.getInt(i));
column.putLong(i, ParquetRowConverter.binaryToSQLTimestamp(v));
}
} else {
throw new UnsupportedOperationException();
}
break;
case BINARY:
// TODO: this is incredibly inefficient as it blows up the dictionary right here. We
// need to do this better. We should probably add the dictionary data to the ColumnVector
// and reuse it across batches. This should mean adding a ByteArray would just update
// the length and offset.
for (int i = rowId; i < rowId + num; ++i) {
Binary v = dictionary.decodeToBinary(dictionaryIds.getInt(i));
column.putByteArray(i, v.getBytes());
}
break;
case FIXED_LEN_BYTE_ARRAY:
// DecimalType written in the legacy mode
if (DecimalType.is32BitDecimalType(column.dataType())) {
for (int i = rowId; i < rowId + num; ++i) {
Binary v = dictionary.decodeToBinary(dictionaryIds.getInt(i));
column.putInt(i, (int) ParquetRowConverter.binaryToUnscaledLong(v));
}
} else if (DecimalType.is64BitDecimalType(column.dataType())) {
for (int i = rowId; i < rowId + num; ++i) {
Binary v = dictionary.decodeToBinary(dictionaryIds.getInt(i));
column.putLong(i, ParquetRowConverter.binaryToUnscaledLong(v));
}
} else if (DecimalType.isByteArrayDecimalType(column.dataType())) {
for (int i = rowId; i < rowId + num; ++i) {
Binary v = dictionary.decodeToBinary(dictionaryIds.getInt(i));
column.putByteArray(i, v.getBytes());
}
} else {
throw new UnsupportedOperationException();
}
break;
default:
throw new UnsupportedOperationException("Unsupported type: " + descriptor.getType());
}
}
/** Reads `total` values from this columnReader into column. */
void readBatch(int total, ColumnVector column) throws IOException {
int rowId = 0;
ColumnVector dictionaryIds = null;
if (dictionary != null) {
// SPARK-16334: We only maintain a single dictionary per row batch, so that it can be used to
// decode all previous dictionary encoded pages if we ever encounter a non-dictionary encoded
// page.
dictionaryIds = column.reserveDictionaryIds(total);
}
while (total > 0) {
// Compute the number of values we want to read in this page.
int leftInPage = (int) (endOfPageValueCount - valuesRead);
if (leftInPage == 0) {
readPage();
leftInPage = (int) (endOfPageValueCount - valuesRead);
}
int num = Math.min(total, leftInPage);
if (isCurrentPageDictionaryEncoded) {
// Read and decode dictionary ids.
defColumn.readIntegers(
num, dictionaryIds, column, rowId, maxDefLevel, (VectorizedValuesReader) dataColumn);
if (column.hasDictionary()
|| (rowId == 0
&& (descriptor.getType() == PrimitiveType.PrimitiveTypeName.INT32
|| descriptor.getType() == PrimitiveType.PrimitiveTypeName.INT64
|| descriptor.getType() == PrimitiveType.PrimitiveTypeName.FLOAT
|| descriptor.getType() == PrimitiveType.PrimitiveTypeName.DOUBLE
|| descriptor.getType() == PrimitiveType.PrimitiveTypeName.BINARY))) {
// Column vector supports lazy decoding of dictionary values so just set the dictionary.
// We can't do this if rowId != 0 AND the column doesn't have a dictionary (i.e. some
// non-dictionary encoded values have already been added).
column.setDictionary(dictionary);
} else {
decodeDictionaryIds(rowId, num, column, dictionaryIds);
}
} else {
if (column.hasDictionary() && rowId != 0) {
// This batch already has dictionary encoded values but this new page is not. The batch
// does not support a mix of dictionary and not so we will decode the dictionary.
decodeDictionaryIds(0, rowId, column, column.getDictionaryIds());
}
column.setDictionary(null);
switch (descriptor.getType()) {
case BOOLEAN:
readBooleanBatch(rowId, num, column);
break;
case INT32:
readIntBatch(rowId, num, column);
break;
case INT64:
readLongBatch(rowId, num, column);
break;
case INT96:
readBinaryBatch(rowId, num, column);
break;
case FLOAT:
readFloatBatch(rowId, num, column);
break;
case DOUBLE:
readDoubleBatch(rowId, num, column);
break;
case BINARY:
readBinaryBatch(rowId, num, column);
break;
case FIXED_LEN_BYTE_ARRAY:
readFixedLenByteArrayBatch(rowId, num, column, descriptor.getTypeLength());
break;
default:
throw new IOException("Unsupported type: " + descriptor.getType());
}
}
valuesRead += num;
rowId += num;
total -= num;
}
}
