[
https://issues.apache.org/jira/browse/HIVE-26221?focusedWorklogId=832837&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-832837
]
ASF GitHub Bot logged work on HIVE-26221:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 12/Dec/22 17:58
Start Date: 12/Dec/22 17:58
Worklog Time Spent: 10m
Work Description: amansinha100 commented on code in PR #3137:
URL: https://github.com/apache/hive/pull/3137#discussion_r1046190045
##########
ql/src/java/org/apache/hadoop/hive/ql/optimizer/stats/annotation/StatsRulesProcFactory.java:
##########
@@ -1234,17 +1285,70 @@ private long evaluateComparator(Statistics stats,
AnnotateStatsProcCtx aspCtx, E
// new estimate for the number of rows
return Math.round(
((maxValue.subtract(value)).divide(maxValue.subtract(minValue),
RoundingMode.UP))
- .multiply(BigDecimal.valueOf(numRows))
+ .multiply(BigDecimal.valueOf(currNumRows))
.doubleValue());
}
}
}
} catch (NumberFormatException nfe) {
- return numRows / 3;
+ return currNumRows / 3;
}
}
// default
- return numRows / 3;
+ return currNumRows / 3;
+ }
+
+ private long evaluateComparatorWithHistogram(ColStatistics cs, long
currNumRows, String colTypeLowerCase,
+ String boundValue, boolean upperBound, boolean closedBound) {
+ final KllFloatsSketch kll =
KllFloatsSketch.heapify(Memory.wrap(cs.getHistogram()));
+
+ if (kll.getN() == 0) {
+ return 0;
+ }
+
+ try {
+ final float value = extractFloatFromLiteralValue(colTypeLowerCase,
boundValue);
+
+ // kll ignores null values (i.e., kll.getN() + numNulls =
currNumRows), we therefore need to use kll.getN()
+ // instead of currNumRows since the CDF is expressed as a fraction of
kll.getN(), not currNumRows
+ if (upperBound) {
+ return Math.round(kll.getN() * (closedBound ?
+ lessThanOrEqualSelectivity(kll, value) :
lessThanSelectivity(kll, value)));
+ } else {
+ return Math.round(kll.getN() * (closedBound ?
+ greaterThanOrEqualSelectivity(kll, value) :
greaterThanSelectivity(kll, value)));
+ }
+ } catch (RuntimeException e) {
+ LOG.debug("Selectivity computation using histogram failed to parse the
boundary value ({}), "
+ + ", using the generic computation strategy", boundValue, e);
+ return currNumRows / 3;
+ }
+ }
+
+ @VisibleForTesting
+ protected static float extractFloatFromLiteralValue(String
colTypeLowerCase, String value) {
+ if (colTypeLowerCase.equals(serdeConstants.TINYINT_TYPE_NAME)) {
+ return Byte.parseByte(value);
+ } else if (colTypeLowerCase.equals(serdeConstants.SMALLINT_TYPE_NAME)) {
+ return Short.parseShort(value);
+ } else if (colTypeLowerCase.equals(serdeConstants.INT_TYPE_NAME)) {
+ return Integer.parseInt(value);
+ } else if (colTypeLowerCase.equals(serdeConstants.BIGINT_TYPE_NAME)) {
+ return Long.parseLong(value);
+ } else if (colTypeLowerCase.equals(serdeConstants.FLOAT_TYPE_NAME)) {
+ return Float.parseFloat(value);
+ } else if (colTypeLowerCase.equals(serdeConstants.DOUBLE_TYPE_NAME)) {
+ return (float) Double.parseDouble(value);
+ } else if
(colTypeLowerCase.startsWith(serdeConstants.DECIMAL_TYPE_NAME)) {
+ return new BigDecimal(value).floatValue();
Review Comment:
Ah, that sounds fine then. I see the rationale for naming it extractFloat..
Issue Time Tracking
-------------------
Worklog Id: (was: 832837)
Time Spent: 10.5h (was: 10h 20m)
> Add histogram-based column statistics
> -------------------------------------
>
> Key: HIVE-26221
> URL: https://issues.apache.org/jira/browse/HIVE-26221
> Project: Hive
> Issue Type: Improvement
> Components: CBO, Metastore, Statistics
> Affects Versions: 4.0.0-alpha-2
> Reporter: Alessandro Solimando
> Assignee: Alessandro Solimando
> Priority: Major
> Labels: pull-request-available
> Time Spent: 10.5h
> Remaining Estimate: 0h
>
> Hive does not support histogram statistics, which are particularly useful for
> skewed data (which is very common in practice) and range predicates.
> Hive's current selectivity estimation for range predicates is based on a
> hard-coded value of 1/3 (see
> [FilterSelectivityEstimator.java#L138-L144|https://github.com/apache/hive/blob/56c336268ea8c281d23c22d89271af37cb7e2572/ql/src/java/org/apache/hadoop/hive/ql/optimizer/calcite/stats/FilterSelectivityEstimator.java#L138-L144]).])
> The current proposal aims at integrating histogram as an additional column
> statistics, stored into the Hive metastore at the table (or partition) level.
> The main requirements for histogram integration are the following:
> * efficiency: the approach must scale and support billions of rows
> * merge-ability: partition-level histograms have to be merged to form
> table-level histograms
> * explicit and configurable trade-off between memory footprint and accuracy
> Hive already integrates [KLL data
> sketches|https://datasketches.apache.org/docs/KLL/KLLSketch.html] UDAF.
> Datasketches are small, stateful programs that process massive data-streams
> and can provide approximate answers, with mathematical guarantees, to
> computationally difficult queries orders-of-magnitude faster than
> traditional, exact methods.
> We propose to use KLL, and more specifically the cumulative distribution
> function (CDF), as the underlying data structure for our histogram statistics.
> The current proposal targets numeric data types (float, integer and numeric
> families) and temporal data types (date and timestamp).
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