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https://issues.apache.org/jira/browse/HIVE-25193?focusedWorklogId=635659&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-635659
]
ASF GitHub Bot logged work on HIVE-25193:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 08/Aug/21 00:09
Start Date: 08/Aug/21 00:09
Worklog Time Spent: 10m
Work Description: github-actions[bot] commented on pull request #2358:
URL: https://github.com/apache/hive/pull/2358#issuecomment-894721225
This pull request has been automatically marked as stale because it has not
had recent activity. It will be closed if no further activity occurs.
Feel free to reach out on the [email protected] list if the patch is in
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Issue Time Tracking
-------------------
Worklog Id: (was: 635659)
Time Spent: 20m (was: 10m)
> Vectorized Query Execution: ClassCastException when use nvl() function which
> default_value is decimal type
> ----------------------------------------------------------------------------------------------------------
>
> Key: HIVE-25193
> URL: https://issues.apache.org/jira/browse/HIVE-25193
> Project: Hive
> Issue Type: Bug
> Components: Vectorization
> Affects Versions: 4.0.0
> Reporter: qiang.bi
> Assignee: qiang.bi
> Priority: Major
> Labels: pull-request-available
> Attachments: HIVE-25193.1.patch
>
> Time Spent: 20m
> Remaining Estimate: 0h
>
> Problem statement:
> {code:java}
> set hive.vectorized.execution.enabled = true;
> select nvl(get_json_object(attr_json,'$.correctedPrice'),0.88)
> corrected_price from dw_mdm_sync_asset;
> {code}
> The error log:
> {code:java}
> Caused by: java.lang.ClassCastException:
> org.apache.hadoop.hive.ql.exec.vector.DecimalColumnVector cannot be cast to
> org.apache.hadoop.hive.ql.exec.vector.BytesColumnVectorCaused by:
> java.lang.ClassCastException:
> org.apache.hadoop.hive.ql.exec.vector.DecimalColumnVector cannot be cast to
> org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector at
> org.apache.hadoop.hive.ql.exec.vector.BytesColumnVector.setElement(BytesColumnVector.java:504)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.VectorCoalesce.evaluate(VectorCoalesce.java:124)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.VectorExpression.evaluateChildren(VectorExpression.java:271)
> at
> org.apache.hadoop.hive.ql.exec.vector.expressions.CastStringToDouble.evaluate(CastStringToDouble.java:83)
> at
> org.apache.hadoop.hive.ql.exec.vector.VectorSelectOperator.process(VectorSelectOperator.java:146)
> ... 28 more{code}
> The problem HiveQL:
> {code:java}
> nvl(get_json_object(attr_json,'$.correctedPrice'),0.88) corrected_price
> {code}
> The problem expression:
> {code:java}
> CastStringToDouble(col 39:string)(children: VectorCoalesce(columns [37,
> 38])(children: VectorUDFAdaptor(get_json_object(_col14, '$.correctedPrice'))
> -> 37:string, ConstantVectorExpression(val 0.88) -> 38:decimal(2,2)) ->
> 39:string) -> 40:double
> {code}
> The problem code:
> {code:java}
> public class VectorCoalesce extends VectorExpression {
> ...
> @Override
> public void evaluate(VectorizedRowBatch batch) throws HiveException { if
> (childExpressions != null) {
> super.evaluateChildren(batch);
> } int[] sel = batch.selected;
> int n = batch.size;
> ColumnVector outputColVector = batch.cols[outputColumnNum];
> boolean[] outputIsNull = outputColVector.isNull;
> if (n <= 0) {
> // Nothing to do
> return;
> } if (unassignedBatchIndices == null || n >
> unassignedBatchIndices.length) { // (Re)allocate larger to be a multiple
> of 1024 (DEFAULT_SIZE).
> final int roundUpSize =
> ((n + VectorizedRowBatch.DEFAULT_SIZE - 1) /
> VectorizedRowBatch.DEFAULT_SIZE)
> * VectorizedRowBatch.DEFAULT_SIZE;
> unassignedBatchIndices = new int[roundUpSize];
> } // We do not need to do a column reset since we are carefully
> changing the output.
> outputColVector.isRepeating = false; // CONSIDER: Should be do this
> for all vector expressions that can
> // work on BytesColumnVector output columns???
> outputColVector.init();
> final int columnCount = inputColumns.length; /*
> * Process the input columns to find a non-NULL value for each row.
> *
> * We track the unassigned batchIndex of the rows that have not received
> * a non-NULL value yet. Similar to a selected array.
> */
> boolean isAllUnassigned = true;
> int unassignedColumnCount = 0;
> for (int k = 0; k < inputColumns.length; k++) {
> ColumnVector cv = batch.cols[inputColumns[k]];
> if (cv.isRepeating) { if (cv.noNulls || !cv.isNull[0]) {
> /*
> * With a repeating value we can finish all remaining rows.
> */
> if (isAllUnassigned) { // No other columns provided
> non-NULL values. We can return repeated output.
> outputIsNull[0] = false;
> outputColVector.setElement(0, 0, cv);
> outputColVector.isRepeating = true;
> return;
> } else { // Some rows have already been assigned values.
> Assign the remaining.
> // We cannot use copySelected method here.
> for (int i = 0; i < unassignedColumnCount; i++) {
> final int batchIndex = unassignedBatchIndices[i];
> outputIsNull[batchIndex] = false; // Our input is
> repeating (i.e. inputColNumber = 0).
> outputColVector.setElement(batchIndex, 0, cv);
> }
> return;
> }
> } else { // Repeated NULLs -- skip this input column.
> }
> } else { /*
> * Non-repeating input column. Use any non-NULL values for unassigned
> rows.
> */
> if (isAllUnassigned) { /*
> * No other columns provided non-NULL values. We *may* be able to
> finish all rows
> * with this input column...
> */
> if (cv.noNulls){ // Since no NULLs, we can provide
> values for all rows.
> if (batch.selectedInUse) {
> for (int i = 0; i < n; i++) {
> final int batchIndex = sel[i];
> outputIsNull[batchIndex] = false;
> outputColVector.setElement(batchIndex, batchIndex, cv);
> }
> } else {
> Arrays.fill(outputIsNull, 0, n, false);
> for (int batchIndex = 0; batchIndex < n; batchIndex++) {
> outputColVector.setElement(batchIndex, batchIndex, cv);
> }
> }
> return;
> } else { // We might not be able to assign all rows
> because of input NULLs. Start tracking any
> // unassigned rows.
> boolean[] inputIsNull = cv.isNull;
> if (batch.selectedInUse) {
> for (int i = 0; i < n; i++) {
> final int batchIndex = sel[i];
> if (!inputIsNull[batchIndex]) {
> outputIsNull[batchIndex] = false;
> outputColVector.setElement(batchIndex, batchIndex, cv);
> } else {
> unassignedBatchIndices[unassignedColumnCount++] =
> batchIndex;
> }
> }
> } else {
> for (int batchIndex = 0; batchIndex < n; batchIndex++) {
> if (!inputIsNull[batchIndex]) {
> outputIsNull[batchIndex] = false;
> outputColVector.setElement(batchIndex, batchIndex, cv);
> } else {
> unassignedBatchIndices[unassignedColumnCount++] =
> batchIndex;
> }
> }
> }
> if (unassignedColumnCount == 0) {
> return;
> }
> isAllUnassigned = false;
> }
> } else { /*
> * We previously assigned *some* rows with non-NULL values. The
> batch indices of
> * the unassigned row were tracked.
> */
> if (cv.noNulls) { // Assign all remaining rows.
> for (int i = 0; i < unassignedColumnCount; i++) {
> final int batchIndex = unassignedBatchIndices[i];
> outputIsNull[batchIndex] = false;
> outputColVector.setElement(batchIndex, batchIndex, cv);
> }
> return;
> } else { // Use any non-NULL values found; remember the
> remaining unassigned.
> boolean[] inputIsNull = cv.isNull;
> int newUnassignedColumnCount = 0;
> for (int i = 0; i < unassignedColumnCount; i++) {
> final int batchIndex = unassignedBatchIndices[i];
> if (!inputIsNull[batchIndex]) {
> outputIsNull[batchIndex] = false;
> outputColVector.setElement(batchIndex, batchIndex, cv);
> } else {
> unassignedBatchIndices[newUnassignedColumnCount++] =
> batchIndex;
> }
> }
> if (newUnassignedColumnCount == 0) {
> return;
> }
> unassignedColumnCount = newUnassignedColumnCount;
> }
> }
> }
> } // NULL out the remaining columns.
> outputColVector.noNulls = false;
> if (isAllUnassigned) {
> outputIsNull[0] = true;
> outputColVector.isRepeating = true;
> } else {
> for (int i = 0; i < unassignedColumnCount; i++) {
> final int batchIndex = unassignedBatchIndices[i];
> outputIsNull[batchIndex] = true;
> }
> }
> }
> ...
> }
> {code}
> The above code, outputColVector is BytesColumnVector type, but one of the
> columnVector is DecimalColumnVector type.
> At present, we can add single quotes in “0.88” to resolve this problem.For
> example:
> {code:java}
> nvl(get_json_object(attr_json,'$.correctedPrice'), '0.88') corrected_price
> {code}
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