@Override
public void write(NullWritable nullWritable, V v) throws IOException {
// if the batch is full, write it out.
if (batch.size == batch.getMaxSize()) {
writer.addRowBatch(batch);
batch.reset();
}
// add the new row
int row = batch.size++;
// skip over the OrcKey or OrcValue
if (v instanceof OrcKey) {
v = (V) ((OrcKey) v).key;
} else if (v instanceof OrcValue) {
v = (V) ((OrcValue) v).value;
}
if (isTopStruct) {
for (int f = 0; f < schema.getChildren().size(); ++f) {
OrcMapredRecordWriter.setColumn(
schema.getChildren().get(f), batch.cols[f], row, ((OrcStruct) v).getFieldValue(f));
}
} else {
OrcMapredRecordWriter.setColumn(schema, batch.cols[0], row, v);
}
}
/*
* Input array is used to fill the entire size of the vector row batch
*/
private VectorizedRowBatch getVectorizedRowBatch(int[] inputs, int size) {
VectorizedRowBatch batch = new VectorizedRowBatch(2, size);
LongColumnVector lcv = new LongColumnVector(size);
for (int i = 0; i < size; i++) {
lcv.vector[i] = inputs[i % inputs.length];
}
batch.cols[0] = lcv;
batch.cols[1] = new LongColumnVector(size);
batch.size = size;
return batch;
}
private VectorizedRowBatch getVectorizedRandomRowBatch(int seed, int size) {
VectorizedRowBatch batch = new VectorizedRowBatch(2, size);
LongColumnVector lcv = new LongColumnVector(size);
Random rand = new Random(seed);
for (int i = 0; i < size; i++) {
lcv.vector[i] = (rand.nextInt());
}
batch.cols[0] = lcv;
batch.cols[1] = new LongColumnVector(size);
batch.size = size;
return batch;
}
/**
* @param values
* @return true if it is not done and can take more inputs
*/
private <E> boolean processVectors(Iterator<E> values, byte tag) throws HiveException {
VectorizedRowBatch batch = batches[tag];
batch.reset();
/* deserialize key into columns */
VectorizedBatchUtil.addRowToBatchFrom(keyObject, keyStructInspector, 0, 0, batch, buffer);
for (int i = 0; i < keysColumnOffset; i++) {
VectorizedBatchUtil.setRepeatingColumn(batch, i);
}
int rowIdx = 0;
try {
while (values.hasNext()) {
/* deserialize value into columns */
BytesWritable valueWritable = (BytesWritable) values.next();
Object valueObj = deserializeValue(valueWritable, tag);
VectorizedBatchUtil.addRowToBatchFrom(
valueObj, valueStructInspectors[tag], rowIdx, keysColumnOffset, batch, buffer);
rowIdx++;
if (rowIdx >= BATCH_SIZE) {
VectorizedBatchUtil.setBatchSize(batch, rowIdx);
reducer.process(batch, tag);
rowIdx = 0;
if (isLogInfoEnabled) {
logMemoryInfo();
}
}
}
if (rowIdx > 0) {
VectorizedBatchUtil.setBatchSize(batch, rowIdx);
reducer.process(batch, tag);
}
if (isLogInfoEnabled) {
logMemoryInfo();
}
} catch (Exception e) {
String rowString = null;
try {
rowString = batch.toString();
} catch (Exception e2) {
rowString =
"[Error getting row data with exception " + StringUtils.stringifyException(e2) + " ]";
}
throw new HiveException(
"Error while processing vector batch (tag=" + tag + ") " + rowString, e);
}
return true; // give me more
}
@Override
public void evaluate(VectorizedRowBatch batch) {
int n = batch.size;
if (n <= 0) {
return;
}
VectorExpression childExpr1 = this.childExpressions[0];
boolean prevSelectInUse = batch.selectedInUse;
// Save the original selected vector
int[] sel = batch.selected;
if (batch.selectedInUse) {
System.arraycopy(sel, 0, initialSelected, 0, n);
} else {
for (int i = 0; i < n; i++) {
initialSelected[i] = i;
sel[i] = i;
}
batch.selectedInUse = true;
}
childExpr1.evaluate(batch);
// Preserve the selected reference and size values generated
// after the first child is evaluated.
int sizeAfterFirstChild = batch.size;
int[] selectedAfterFirstChild = batch.selected;
// Calculate unselected ones in last evaluate.
for (int j = 0; j < n; j++) {
tmp[initialSelected[j]] = 0;
}
for (int j = 0; j < batch.size; j++) {
tmp[selectedAfterFirstChild[j]] = 1;
}
int unselectedSize = 0;
for (int j = 0; j < n; j++) {
int i = initialSelected[j];
if (tmp[i] == 0) {
unselected[unselectedSize++] = i;
}
}
int newSize = sizeAfterFirstChild;
batch.selected = unselected;
batch.size = unselectedSize;
if (unselectedSize > 0) {
// Evaluate subsequent child expression over unselected ones only.
final int childrenCount = this.childExpressions.length;
int childIndex = 1;
while (true) {
boolean isLastChild = (childIndex + 1 >= childrenCount);
// When we have yet another child beyond the current one... save unselected.
if (!isLastChild) {
System.arraycopy(batch.selected, 0, unselectedCopy, 0, unselectedSize);
}
VectorExpression childExpr = this.childExpressions[childIndex];
childExpr.evaluate(batch);
// Merge the result of last evaluate to previous evaluate.
newSize += batch.size;
for (int i = 0; i < batch.size; i++) {
tmp[batch.selected[i]] = 1;
}
if (isLastChild) {
break;
}
unselectedSize =
subtract(unselectedCopy, unselectedSize, batch.selected, batch.size, difference);
if (unselectedSize == 0) {
break;
}
System.arraycopy(difference, 0, batch.selected, 0, unselectedSize);
batch.size = unselectedSize;
childIndex++;
}
}
// Important: Restore the batch's selected array.
batch.selected = selectedAfterFirstChild;
int k = 0;
for (int j = 0; j < n; j++) {
int i = initialSelected[j];
if (tmp[i] == 1) {
batch.selected[k++] = i;
}
}
batch.size = newSize;
if (newSize == n) {
// Filter didn't do anything
batch.selectedInUse = prevSelectInUse;
}
}
@Override
public void process(Object row, int tag) throws HiveException {
try {
VectorizedRowBatch batch = (VectorizedRowBatch) row;
alias = (byte) tag;
if (needCommonSetup) {
// Our one time process method initialization.
commonSetup(batch);
/*
* Initialize Single-Column String members for this specialized class.
*/
singleJoinColumn = bigTableKeyColumnMap[0];
needCommonSetup = false;
}
if (needHashTableSetup) {
// Setup our hash table specialization. It will be the first time the process
// method is called, or after a Hybrid Grace reload.
/*
* Get our Single-Column String hash map information for this specialized class.
*/
hashMap = (VectorMapJoinBytesHashMap) vectorMapJoinHashTable;
needHashTableSetup = false;
}
batchCounter++;
// Do the per-batch setup for an outer join.
outerPerBatchSetup(batch);
// For outer join, DO NOT apply filters yet. It is incorrect for outer join to
// apply the filter before hash table matching.
final int inputLogicalSize = batch.size;
if (inputLogicalSize == 0) {
if (LOG.isDebugEnabled()) {
LOG.debug(CLASS_NAME + " batch #" + batchCounter + " empty");
}
return;
}
// Perform any key expressions. Results will go into scratch columns.
if (bigTableKeyExpressions != null) {
for (VectorExpression ve : bigTableKeyExpressions) {
ve.evaluate(batch);
}
}
// We rebuild in-place the selected array with rows destine to be forwarded.
int numSel = 0;
/*
* Single-Column String specific declarations.
*/
// The one join column for this specialized class.
BytesColumnVector joinColVector = (BytesColumnVector) batch.cols[singleJoinColumn];
byte[][] vector = joinColVector.vector;
int[] start = joinColVector.start;
int[] length = joinColVector.length;
/*
* Single-Column String check for repeating.
*/
// Check single column for repeating.
boolean allKeyInputColumnsRepeating = joinColVector.isRepeating;
if (allKeyInputColumnsRepeating) {
/*
* Repeating.
*/
// All key input columns are repeating. Generate key once. Lookup once.
// Since the key is repeated, we must use entry 0 regardless of selectedInUse.
/*
* Single-Column String specific repeated lookup.
*/
JoinUtil.JoinResult joinResult;
if (!joinColVector.noNulls && joinColVector.isNull[0]) {
// Null key is no match for whole batch.
joinResult = JoinUtil.JoinResult.NOMATCH;
} else {
// Handle *repeated* join key, if found.
byte[] keyBytes = vector[0];
int keyStart = start[0];
int keyLength = length[0];
joinResult = hashMap.lookup(keyBytes, keyStart, keyLength, hashMapResults[0]);
}
/*
* Common repeated join result processing.
*/
if (LOG.isDebugEnabled()) {
LOG.debug(
CLASS_NAME + " batch #" + batchCounter + " repeated joinResult " + joinResult.name());
}
numSel = finishOuterRepeated(batch, joinResult, hashMapResults[0], scratch1);
} else {
/*
* NOT Repeating.
*/
if (LOG.isDebugEnabled()) {
LOG.debug(CLASS_NAME + " batch #" + batchCounter + " non-repeated");
}
int selected[] = batch.selected;
boolean selectedInUse = batch.selectedInUse;
// For outer join we must apply the filter after match and cause some matches to become
// non-matches, we do not track non-matches here. Instead we remember all non spilled rows
// and compute non matches later in finishOuter.
int hashMapResultCount = 0;
int matchCount = 0;
int nonSpillCount = 0;
int spillCount = 0;
/*
* Single-Column String specific variables.
*/
int saveKeyBatchIndex = -1;
// We optimize performance by only looking up the first key in a series of equal keys.
boolean haveSaveKey = false;
JoinUtil.JoinResult saveJoinResult = JoinUtil.JoinResult.NOMATCH;
// Logical loop over the rows in the batch since the batch may have selected in use.
for (int logical = 0; logical < inputLogicalSize; logical++) {
int batchIndex = (selectedInUse ? selected[logical] : logical);
/*
* Single-Column String outer null detection.
*/
boolean isNull = !joinColVector.noNulls && joinColVector.isNull[batchIndex];
if (isNull) {
// Have that the NULL does not interfere with the current equal key series, if there
// is one. We do not set saveJoinResult.
//
// Let a current MATCH equal key series keep going, or
// Let a current SPILL equal key series keep going, or
// Let a current NOMATCH keep not matching.
// Remember non-matches for Outer Join.
nonSpills[nonSpillCount++] = batchIndex;
// LOG.debug(CLASS_NAME + " logical " + logical + " batchIndex " + batchIndex + "
// NULL");
} else {
/*
* Single-Column String outer get key.
*/
// Implicit -- use batchIndex.
/*
* Equal key series checking.
*/
if (!haveSaveKey
|| StringExpr.compare(
vector[saveKeyBatchIndex],
start[saveKeyBatchIndex],
length[saveKeyBatchIndex],
vector[batchIndex],
start[batchIndex],
length[batchIndex])
!= 0) {
// New key.
if (haveSaveKey) {
// Move on with our count(s).
switch (saveJoinResult) {
case MATCH:
case SPILL:
hashMapResultCount++;
break;
case NOMATCH:
break;
}
}
// Regardless of our matching result, we keep that information to make multiple use
// of it for a possible series of equal keys.
haveSaveKey = true;
/*
* Single-Column String specific save key.
*/
saveKeyBatchIndex = batchIndex;
/*
* Single-Column Long specific lookup key.
*/
byte[] keyBytes = vector[batchIndex];
int keyStart = start[batchIndex];
int keyLength = length[batchIndex];
saveJoinResult =
hashMap.lookup(keyBytes, keyStart, keyLength, hashMapResults[hashMapResultCount]);
// LOG.debug(CLASS_NAME + " logical " + logical + " batchIndex " + batchIndex + " New
// Key " + saveJoinResult.name());
} else {
// LOG.debug(CLASS_NAME + " logical " + logical + " batchIndex " + batchIndex + " Key
// Continues " + saveJoinResult.name());
}
/*
* Common outer join result processing.
*/
switch (saveJoinResult) {
case MATCH:
matchs[matchCount] = batchIndex;
matchHashMapResultIndices[matchCount] = hashMapResultCount;
matchCount++;
nonSpills[nonSpillCount++] = batchIndex;
break;
case SPILL:
spills[spillCount] = batchIndex;
spillHashMapResultIndices[spillCount] = hashMapResultCount;
spillCount++;
break;
case NOMATCH:
nonSpills[nonSpillCount++] = batchIndex;
// VectorizedBatchUtil.debugDisplayOneRow(batch, batchIndex, CLASS_NAME + " NOMATCH
// duplicate");
break;
}
}
}
if (haveSaveKey) {
// Account for last equal key sequence.
switch (saveJoinResult) {
case MATCH:
case SPILL:
hashMapResultCount++;
break;
case NOMATCH:
break;
}
}
if (LOG.isDebugEnabled()) {
LOG.debug(
CLASS_NAME
+ " batch #"
+ batchCounter
+ " matchs "
+ intArrayToRangesString(matchs, matchCount)
+ " matchHashMapResultIndices "
+ intArrayToRangesString(matchHashMapResultIndices, matchCount)
+ " nonSpills "
+ intArrayToRangesString(nonSpills, nonSpillCount)
+ " spills "
+ intArrayToRangesString(spills, spillCount)
+ " spillHashMapResultIndices "
+ intArrayToRangesString(spillHashMapResultIndices, spillCount)
+ " hashMapResults "
+ Arrays.toString(Arrays.copyOfRange(hashMapResults, 0, hashMapResultCount)));
}
// We will generate results for all matching and non-matching rows.
// Note that scratch1 is undefined at this point -- it's preallocated storage.
numSel =
finishOuter(
batch,
matchs,
matchHashMapResultIndices,
matchCount,
nonSpills,
nonSpillCount,
spills,
spillHashMapResultIndices,
spillCount,
hashMapResults,
hashMapResultCount,
scratch1);
}
batch.selectedInUse = true;
batch.size = numSel;
if (batch.size > 0) {
// Forward any remaining selected rows.
forwardBigTableBatch(batch);
}
} catch (IOException e) {
throw new HiveException(e);
} catch (Exception e) {
throw new HiveException(e);
}
}