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https://issues.apache.org/jira/browse/HUDI-2369?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17408414#comment-17408414
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ASF GitHub Bot commented on HUDI-2369:
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vinothchandar commented on a change in pull request #3549:
URL: https://github.com/apache/hudi/pull/3549#discussion_r700624615
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File path: website/blog/2021-08-27-bulk-insert-sort-modes.md
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@@ -0,0 +1,88 @@
+---
+title: "Bulk Insert Sort Modes with Apache Hudi"
+excerpt: "Different sort modes available with BulkInsert"
+author: shivnarayan
+category: blog
+---
+
+Apache Hudi supports a `bulk_insert` operation in addition to "insert" and
"upsert" to ingest data into a hudi table.
+There are different sort modes that one could employ while using bulk_insert.
This blog will talk about
+different sort modes available out of the box, and how each compares with
others.
+<!--truncate-->
+
+Apache Hudi supports “bulk_insert” to assist in initial loading to data to a
hudi table. This is expected
+to be faster when compared to using “insert” or “upsert” operations. Bulk
insert differs from insert in two
+aspects. Existing records are never looked up with bulk_insert, and some
writer side optimizations like
+small files are not managed with bulk_insert.
+
+Bulk insert offers 3 different sort modes to cater to different needs of
users, based on the following principles.
+
+- Sorting will give us good compression and upsert performance, if data is
laid out well. Especially if your record keys
+ have some sort of ordering (timestamp, etc) characteristics, sorting will
assist in trimming down a lot of files
+ during upsert. If data is sorted by frequently queried columns, queries will
leverage parquet predicate pushdown
+ to trim down the data to ensure lower latency as well.
+
+- Additionally, parquet writing is quite a memory intensive operation. When
writing large volumes of data into a table
+ that is also partitioned into 1000s of partitions, without sorting of any
kind, the writer may have to keep 1000s of
+ parquet writers open simultaneously incurring unsustainable memory pressure
and eventually leading to crashes.
+
+- It's also desirable to start with the smallest amount of files possible when
bulk importing data, as to avoid
+ metadata overhead later on for writers and queries.
+
+3 Sort modes supported out of the box are: `PARTITION_SORT`,`GLOBAL_SORT` and
`NONE`.
+
+## Configurations
+One can set the config
[“hoodie.bulkinsert.sort.mode”](https://hudi.apache.org/docs/configurations.html#withBulkInsertSortMode)
to either
+of the three values, namely NONE, GLOBAL_SORT and PARTITION_SORT. Default sort
mode is `GLOBAL_SORT`.
+
+## Different Sort Modes
+
+### Global Sort
+
+As the name suggests, Hudi sorts the records globally across the input
partitions, which maximizes the number of files
+pruned using key ranges, during index lookups for subsequent upserts. This is
because each file has non-overlapping
+min, max values for keys, which really helps, when the key has some ordering
characteristics such as a time based prefix.
+Given we are writing to a single parquet file on a single output partition
path on storage at any given time, this mode
+greatly helps control memory pressure during large partitioned writes. Also
due to global sorting, each small table
+partition path will be written from atmost two spark partition and thus
contain just 2 files.
+This is the default sort mode with bulk_insert operation in Hudi.
+
+### Partition sort
+In this sort mode, records within a given spark partition will be sorted. But
there are chances that a given spark partition
+can contain records from different table partitions. And so, even though we
sort within each spark partitions, this sort
+mode could result in large number of files at the end of bulk_insert, since
records for a given table partition could
+be spread across many spark partitions. During actual write by the writers, we
may not have much open files
+simultaneously, since we close out the file before moving to next file (as
records are sorted within a spark partition)
+and hence may not have much memory pressure.
+
+### None
+
+In this mode, no transformation such as sorting is done to the user records
and delegated to the writers as is. So,
+when writing large volumes of data into a table partitioned into 1000s of
partitions, the writer may have to keep 1000s of
+parquet writers open simultaneously incurring unsustainable memory pressure
and eventually leading to crashes. Also,
+min max ranges for a given file could be very wide (unsorted records) and
hence subsequent upserts may read
+bloom filters from lot of files during index lookup. Since records are not
sorted, and each writer could get records
+across N number of table partitions, this sort mode could result in a huge
number of files at the end of bulk import.
+This could also impact your upsert or query performance due to large number of
small files.
+
+## User defined partitioner
+
+If none of the above built-in sort modes suffice, users can also choose to
implement their own
+[partitioner](https://github.com/apache/hudi/blob/master/hudi-client/hudi-client-common/src/main/java/org/apache/hudi/table/BulkInsertPartitioner.java)
+and plug it in with bulk insert as needed.
+
+## Bulk insert with different sort modes
+Here is a microbenchmark to show the performance difference between different
sort modes.
+
+ <br/>
Review comment:
its a bit misleading how sorting adds very little overhead for
bulk_insert. thoughts?
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> Blog on bulk insert sort modes
> ------------------------------
>
> Key: HUDI-2369
> URL: https://issues.apache.org/jira/browse/HUDI-2369
> Project: Apache Hudi
> Issue Type: Improvement
> Components: Docs
> Reporter: sivabalan narayanan
> Priority: Major
> Labels: pull-request-available
> Fix For: 0.10.0
>
>
> Blog on bulk insert sort modes
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