huaxingao commented on code in PR #10659:
URL: https://github.com/apache/iceberg/pull/10659#discussion_r1693697463
##########
spark/v3.5/spark/src/main/java/org/apache/iceberg/spark/source/SparkScan.java:
##########
@@ -175,7 +185,46 @@ public Statistics estimateStatistics() {
protected Statistics estimateStatistics(Snapshot snapshot) {
// its a fresh table, no data
if (snapshot == null) {
- return new Stats(0L, 0L);
+ return new Stats(0L, 0L, Collections.emptyMap());
+ }
+
+ boolean cboEnabled =
+ Boolean.parseBoolean(spark.conf().get(SQLConf.CBO_ENABLED().key(),
"false"));
+ Map<NamedReference, ColumnStatistics> colStatsMap = null;
+ if (readConf.reportColumnStats() && cboEnabled) {
+ colStatsMap = Maps.newHashMap();
+ List<StatisticsFile> files = table.statisticsFiles();
+ if (!files.isEmpty()) {
+ List<BlobMetadata> metadataList = (files.get(0)).blobMetadata();
+
+ for (BlobMetadata blobMetadata : metadataList) {
+ int id = blobMetadata.fields().get(0);
+ String colName = table.schema().findColumnName(id);
+ NamedReference ref = FieldReference.column(colName);
+
+ Long ndv = null;
+ if (blobMetadata
+ .type()
+
.equals(org.apache.iceberg.puffin.StandardBlobTypes.APACHE_DATASKETCHES_THETA_V1))
{
+ String ndvStr = blobMetadata.properties().get(NDV_KEY);
+ if (ndvStr != null && !ndvStr.isEmpty()) {
+ ndv = Long.parseLong(ndvStr);
+ } else {
+ LOG.debug("ndv is not set in BlobMetadata for column {}",
colName);
+ }
+ } else {
+ LOG.debug("DataSketch blob is not available for column {}",
colName);
+ }
+
+ // TODO: Fill min, max and null from the manifest file
Review Comment:
Created [issue](https://github.com/apache/iceberg/issues/10791)
##########
spark/v3.5/spark/src/test/java/org/apache/iceberg/spark/source/TestSparkScan.java:
##########
@@ -130,6 +142,98 @@ public void testEstimatedRowCount() throws
NoSuchTableException {
assertThat(stats.numRows().getAsLong()).isEqualTo(10000L);
}
+ @TestTemplate
+ public void testColStats() throws NoSuchTableException {
+ sql("CREATE TABLE %s (id int, data string) USING iceberg", tableName);
+
+ List<SimpleRecord> records =
+ Lists.newArrayList(
+ new SimpleRecord(1, "a"),
+ new SimpleRecord(2, "b"),
+ new SimpleRecord(3, "a"),
+ new SimpleRecord(4, "b"));
+ spark
+ .createDataset(records, Encoders.bean(SimpleRecord.class))
+ .coalesce(1)
+ .writeTo(tableName)
+ .append();
+
+ Table table = validationCatalog.loadTable(tableIdent);
+ long snapshotId = table.currentSnapshot().snapshotId();
+
+ SparkScanBuilder scanBuilder =
+ new SparkScanBuilder(spark, table, CaseInsensitiveStringMap.empty());
+ SparkScan scan = (SparkScan) scanBuilder.build();
+
+ Map<String, String> reportColStatsDisabled =
+ ImmutableMap.of(
+ SQLConf.CBO_ENABLED().key(), "true",
SparkSQLProperties.REPORT_COLUMN_STATS, "false");
+
+ Map<String, String> reportColStatsEnabled =
+ ImmutableMap.of(SQLConf.CBO_ENABLED().key(), "true");
+
+ // Test table does not have col stats
+ checkColStatisticsNotReported(scan, 4L);
+ withSQLConf(reportColStatsDisabled, () ->
checkColStatisticsNotReported(scan, 4L));
+ // The expected col NDVs are nulls
+ withSQLConf(reportColStatsEnabled, () -> checkColStatisticsReported(scan,
4L, new HashMap<>()));
+
+ GenericStatisticsFile statisticsFile =
+ new GenericStatisticsFile(
+ snapshotId,
+ "/test/statistics/file.puffin",
+ 100,
+ 42,
+ ImmutableList.of(
+ new GenericBlobMetadata(
+ APACHE_DATASKETCHES_THETA_V1,
+ snapshotId,
+ 1,
+ ImmutableList.of(1),
+ ImmutableMap.of("ndv", "4"))));
+
+ table.updateStatistics().setStatistics(snapshotId,
statisticsFile).commit();
+
+ // Test where 1 column has NDV and the other does not have NDV
+ checkColStatisticsNotReported(scan, 4L);
+ withSQLConf(reportColStatsDisabled, () ->
checkColStatisticsNotReported(scan, 4L));
+
+ HashMap<String, Long> expectedOneNDV = new HashMap<>();
+ expectedOneNDV.put("id", 4L);
+ withSQLConf(reportColStatsEnabled, () -> checkColStatisticsReported(scan,
4L, expectedOneNDV));
+
+ statisticsFile =
Review Comment:
Done
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