ZachDischner commented on code in PR #9731:
URL: https://github.com/apache/iceberg/pull/9731#discussion_r1802296391
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api/src/main/java/org/apache/iceberg/actions/RewriteManifests.java:
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@@ -44,6 +47,43 @@ public interface RewriteManifests
*/
RewriteManifests rewriteIf(Predicate<ManifestFile> predicate);
+ /**
+ * Rewrite manifests in a given order, based on partition field names
+ *
+ * <p>Supply an optional set of partition field names to cluster the
rewritten manifests by. For
+ * example, given a table PARTITIONED BY (a, b, c, d), you may wish to
rewrite and cluster
+ * manifests by ('d', 'b') only, based on your query patterns. Rewriting
Manifests in this way
+ * will yield manifest_lists that point to manifest_files containing data
files for common 'd' and
+ * 'b' partitions.
+ *
+ * <p>If not set, manifests will be rewritten in the order of the transforms
in the table's
+ * current partition spec.
+ *
+ * @param partitionFieldClustering Exact transformed column names used for
partitioning; not the
+ * raw column names that partitions are derived from. E.G. supply
'data_bucket' and not 'data'
+ * for a bucket(N, data) partition * definition
+ * @return this for method chaining
+ */
+ default RewriteManifests clusterBy(List<String> partitionFieldClustering) {
+ throw new UnsupportedOperationException(
+ this.getClass().getName() + " doesn't implement
clusterBy(List<String>)");
+ }
+
+ /**
+ * Rewrite manifests in a given order, dictated by a custom Function
+ *
+ * <p>Supply a Function which will apply its own custom clustering logic
based on supplied {@link
+ * org.apache.iceberg.DataFile} attributes.
+ *
+ * @param clusterStrategyFunction A Function that returns a String to be
used for manifest
+ * clustering
+ * @return this method for chaining
+ */
+ default RewriteManifests clusterBy(Function<DataFile, String>
clusterStrategyFunction) {
Review Comment:
I can say that there are reasons to, but it is up to you to decide if they
are very good reasons.
For example, I know that a primary use case for `bucket(someId, 10000)`
partitioned tables will require reading `bucket_someId=1` and
`bucket_someId=999` data together, so I'll want to cluster my planning around
this use case.
Potentially simpler, say I'm partitioning by `month(timestamp)`. I can take
the min/max values of a data file and cluster the files in a given month
partition by day for more efficient query planning. This option lets power
users take what Iceberg gives you to a new level.
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