[
https://issues.apache.org/jira/browse/HIVE-26221?focusedWorklogId=831286&page=com.atlassian.jira.plugin.system.issuetabpanels:worklog-tabpanel#worklog-831286
]
ASF GitHub Bot logged work on HIVE-26221:
-----------------------------------------
Author: ASF GitHub Bot
Created on: 06/Dec/22 07:28
Start Date: 06/Dec/22 07:28
Worklog Time Spent: 10m
Work Description: dengzhhu653 commented on code in PR #3137:
URL: https://github.com/apache/hive/pull/3137#discussion_r1040592119
##########
standalone-metastore/metastore-server/src/test/java/org/apache/hadoop/hive/metastore/StatisticsTestUtils.java:
##########
@@ -109,4 +135,116 @@ public static HyperLogLog createHll(String... values) {
}
return hll;
}
+
+ /**
+ * Creates an HLL object initialized with the given values.
+ * @param values the values to be added
+ * @return an HLL object initialized with the given values.
+ */
+ public static HyperLogLog createHll(double... values) {
+ HyperLogLog hll = HyperLogLog.builder().build();
+ Arrays.stream(values).forEach(hll::addDouble);
+ return hll;
+ }
+
+ /**
+ * Creates a KLL object initialized with the given values.
+ * @param values the values to be added
+ * @return a KLL object initialized with the given values.
+ */
+ public static KllFloatsSketch createKll(float... values) {
+ KllFloatsSketch kll = new KllFloatsSketch();
+ for (float value : values) {
+ kll.update(value);
+ }
+ return kll;
+ }
+
+ /**
+ * Creates a KLL object initialized with the given values.
+ * @param values the values to be added
+ * @return a KLL object initialized with the given values.
+ */
+ public static KllFloatsSketch createKll(double... values) {
+ KllFloatsSketch kll = new KllFloatsSketch();
+ for (double value : values) {
+ kll.update(Double.valueOf(value).floatValue());
+ }
+ return kll;
+ }
+
+ /**
+ * Creates a KLL object initialized with the given values.
+ * @param values the values to be added
+ * @return a KLL object initialized with the given values.
+ */
+ public static KllFloatsSketch createKll(long... values) {
+ KllFloatsSketch kll = new KllFloatsSketch();
+ for (long value : values) {
+ kll.update(value);
+ }
+ return kll;
+ }
+
+ /**
+ * Checks if expected and computed statistics data are equal.
+ * @param expected expected statistics data
+ * @param computed computed statistics data
+ */
+ public static void assertEqualStatistics(ColumnStatisticsData expected,
ColumnStatisticsData computed) {
+ if (expected.getSetField() != computed.getSetField()) {
+ throw new IllegalArgumentException("Expected data is of type " +
expected.getSetField()
+ + " while computed data is of type " + computed.getSetField());
+ }
+
+ Class<?> dataClass = null;
+ switch (expected.getSetField()) {
+ case DATE_STATS:
+ dataClass = DateColumnStatsData.class;
+ break;
+ case LONG_STATS:
+ dataClass = LongColumnStatsData.class;
+ break;
+ case DOUBLE_STATS:
+ dataClass = DoubleColumnStatsData.class;
+ break;
+ case DECIMAL_STATS:
+ dataClass = DecimalColumnStatsData.class;
+ break;
+ case TIMESTAMP_STATS:
+ dataClass = TimestampColumnStatsData.class;
+ break;
+ default:
+ // it's an unsupported class for KLL, no special treatment needed
+ Assert.assertEquals(expected, computed);
+ return;
+ }
+ assertEqualStatistics(expected, computed, dataClass);
+ }
+
+ private static <X> void assertEqualStatistics(
Review Comment:
This function only compares the `histogram`, and does not tell much truth
when either `computedHasHistograms` or `expectedHasHistograms` is false. Cloud
we compare the `ColumnStatisticsData` by `Assert.assertEquals(expected,
computed);` as we did in Line 219?
Issue Time Tracking
-------------------
Worklog Id: (was: 831286)
Time Spent: 4.5h (was: 4h 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: 4.5h
> 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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