[DOCS] Revert download page to its original format to not break searches in website

website/releases/download.md

@@ -11,21 +11,16 @@ last_modified_at: 2022-12-27T15:59:57-04:00
 * Release Note : ([Release Note for Apache Hudi 0.13.1](/releases/release-0.13.1))
 
 ### Release 0.12.3
-* [Long Term Support](/releases/release-0.12.3#long-term-support): this is the latest stable release
+[Long Term Support](/releases/release-0.12.3#long-term-support): this is the latest stable release
 * Source Release : [Apache Hudi 0.12.3 Source Release](https://www.apache.org/dyn/closer.lua/hudi/0.12.3/hudi-0.12.3.src.tgz) ([asc](https://downloads.apache.org/hudi/0.12.3/hudi-0.12.3.src.tgz.asc), [sha512](https://downloads.apache.org/hudi/0.12.3/hudi-0.12.3.src.tgz.sha512))
 * Release Note : ([Release Note for Apache Hudi 0.12.3](/releases/release-0.12.3))
 
 ### Release 0.11.1
 * Source Release : [Apache Hudi 0.11.1 Source Release](https://www.apache.org/dyn/closer.lua/hudi/0.11.1/hudi-0.11.1.src.tgz) ([asc](https://downloads.apache.org/hudi/0.11.1/hudi-0.11.1.src.tgz.asc), [sha512](https://downloads.apache.org/hudi/0.11.1/hudi-0.11.1.src.tgz.sha512))
 * Release Note : ([Release Note for Apache Hudi 0.11.1](/releases/release-0.11.1))
 
-### Release 0.10.1
-* Source Release : [Apache Hudi 0.10.1 Source Release](https://www.apache.org/dyn/closer.lua/hudi/0.10.1/hudi-0.10.1.src.tgz) ([asc](https://downloads.apache.org/hudi/0.10.1/hudi-0.10.1.src.tgz.asc), [sha512](https://downloads.apache.org/hudi/0.10.1/hudi-0.10.1.src.tgz.sha512))
-* Release Note : ([Release Note for Apache Hudi 0.10.1](/releases/release-0.10.1))
-
 ### Older releases
-As new Hudi releases come out for each development stream, previous ones will be archived, but they are still available
-at [here](https://archive.apache.org/dist/hudi/). You can find the release notes of older releases [here](/releases/older-releases).
+As new Hudi releases come out for each development stream, previous ones will be archived, but they are still available at [here](https://archive.apache.org/dist/hudi/). 
 
 ## Verify Release
 

website/releases/release-0.11.0.md

@@ -0,0 +1,220 @@
+---
+title: "Release 0.11.0"
+sidebar_position: 8
+layout: releases
+toc: true
+last_modified_at: 2022-01-27T22:07:00+08:00
+---
+import Tabs from '@theme/Tabs';
+import TabItem from '@theme/TabItem';
+
+## [Release 0.11.0](https://github.com/apache/hudi/releases/tag/release-0.11.0) ([docs](/docs/quick-start-guide))
+
+## Migration Guide
+
+### Bundle usage updates
+
+- Spark bundle for 3.0.x is no longer officially supported. Users are encouraged to upgrade to Spark 3.2 or 3.1.
+- Users are encouraged to use bundles with specific Spark version in the name (`hudi-sparkX.Y-bundle`) and move away
+  from the legacy bundles (`hudi-spark-bundle` and `hudi-spark3-bundle`).
+- Spark or Utilities bundle no longer requires additional `spark-avro` package at runtime; the
+  option `--package org.apache.spark:spark-avro_2.1*:*` can be dropped.
+
+### Configuration updates
+
+- For MOR tables, `hoodie.datasource.write.precombine.field` is required for both write and read.
+- Only set `hoodie.datasource.write.drop.partition.columns=true` when work
+  with [BigQuery integration](/docs/gcp_bigquery).
+- For Spark readers that rely on extracting physical partition path,
+  set `hoodie.datasource.read.extract.partition.values.from.path=true` to stay compatible with existing behaviors.
+- Default index type for Spark was changed from `BLOOM`
+  to `SIMPLE` ([HUDI-3091](https://issues.apache.org/jira/browse/HUDI-3091)). If you currently rely on the default `BLOOM`
+  index type, please update your configuration accordingly.
+
+## Release Highlights
+
+### Multi-Modal Index
+
+In 0.11.0, we enable the [metadata table](/docs/metadata) with synchronous updates and metadata-table-based file listing
+by default for Spark writers, to improve the performance of partition and file listing on large Hudi tables. On the
+reader side, users need to set it to `true` benefit from it. The metadata table and related file listing functionality
+can still be turned off by setting `hoodie.metadata.enable=false`. Due to this, users deploying Hudi with async table
+services need to configure a locking service. If this feature is not relevant for you, you can set
+`hoodie.metadata.enable=false` additionally and use Hudi as before.
+
+We introduce a multi-modal index in metadata table to drastically improve the lookup performance in file index and query
+latency with data skipping. Two new indices are added to the metadata table
+
+1. bloom filter index containing the file-level bloom filter to facilitate key lookup and file pruning as a part of
+   bloom index during upserts by the writers
+2. column stats index containing the statistics of all/interested columns to improve file pruning based on key and
+   column value range in both the writer and the reader, in query planning in Spark for example.
+
+They are disabled by default. You can enable them by setting `hoodie.metadata.index.bloom.filter.enable`
+and `hoodie.metadata.index.column.stats.enable` to `true`, respectively.
+
+*Refer to the [metadata table guide](/docs/metadata#deployment-considerations) for detailed instructions on upgrade and
+deployment.*
+
+### Data Skipping with Metadata Table
+
+With the added support for Column Statistics in metadata table, Data Skipping is now relying on the metadata table's
+Column Stats Index (CSI) instead of its own bespoke index implementation (comparing to Spatial Curves added in 0.10.0),
+allowing to leverage Data Skipping for all datasets regardless of whether they execute layout optimization procedures (
+like clustering) or not. To benefit from Data Skipping, make sure to set `hoodie.enable.data.skipping=true` on both
+writer and reader, as well as enable metadata table and Column Stats Index in the metadata table.
+
+Data Skipping supports standard functions (as well as some common expressions) allowing you to apply common standard
+transformations onto the raw data in your columns within your query's filters. For example, if you have column "ts" that
+stores timestamp as string, you can now query it using human-readable dates in your predicate like
+following: `date_format(ts, "MM/dd/yyyy" ) < "04/01/2022"`.
+
+*Note: Currently Data Skipping is only supported in COW tables and MOR tables in read-optimized mode. The work of full
+support for MOR tables is tracked in [HUDI-3866](https://issues.apache.org/jira/browse/HUDI-3866)*
+
+*Refer to the [performance](/docs/performance#read-path) guide for more info.*
+
+### Async Indexer
+
+In 0.11.0, we added a new asynchronous service for indexing to our rich set of table services. It allows users to create
+different kinds of indices (e.g., files, bloom filters, and column stats) in the metadata table without blocking
+ingestion. The indexer adds a new action `indexing` on the timeline. While the indexing process itself is asynchronous
+and non-blocking to writers, a lock provider needs to be configured to safely co-ordinate the process with the inflight
+writers.
+
+*See the [indexing guide](/docs/metadata_indexing) for more details.*
+
+### Spark DataSource Improvements
+
+Hudi's Spark low-level integration got considerable overhaul consolidating common flows to share the infrastructure and
+bring both compute and data throughput efficiencies when querying the data.
+
+- MOR queries with no log files (except for incremental queries) tables are now leveraging Vectorized Parquet reader while reading
+  the data, meaning that Parquet reader is now able to leverage modern processors vectorized instructions to further
+  speed up decoding of the data. Enabled by default.
+- When standard Record Payload implementation is used (e.g., `OverwriteWithLatestAvroPayload`), MOR table will only
+  fetch *strictly necessary* columns (primary key, pre-combine key) on top of those referenced by the query,
+  substantially reducing wasted data throughput as well as compute spent on decompressing and decoding the data. This is
+  significantly beneficial to "wide" MOR tables with 1000s of columns, for example.
+
+*See the [migration guide](#migration-guide) for the relevant configuration updates.*
+
+### Schema-on-read for Spark
+
+In 0.11.0, users can now easily change the current schema of a Hudi table to adapt to the evolving data schema over
+time. Spark SQL DDL support (experimental) was added for Spark 3.1.x and Spark 3.2.1 via `ALTER TABLE` syntax.
+
+*Please refer to the [schema evolution guide](/docs/schema_evolution) for more details.*
+
+### Spark SQL Improvements
+
+- Users can update or delete records in Hudi tables using non-primary-key fields.
+- Time travel query is now supported via `timestamp as of` syntax. (Spark 3.2+ only)
+- `CALL` command is added to support invoking more actions on Hudi tables.
+
+*Please refer to the [Quick Start - Spark Guide](/docs/quick-start-guide) for more details and examples.*
+
+### Spark Versions and Bundles
+
+- Spark 3.2 support is added; users who are on Spark 3.2 can use `hudi-spark3.2-bundle` or `hudi-spark3-bundle` (legacy bundle name).
+- Spark 3.1 will continue to be supported via `hudi-spark3.1-bundle`.
+- Spark 2.4 will continue to be supported via `hudi-spark2.4-bundle` or `hudi-spark-bundle` (legacy bundle name).
+
+*See the [migration guide](#migration-guide) for usage updates.*
+
+### Slim Utilities Bundle
+
+In 0.11.0, a new `hudi-utilities-slim-bundle` is added to exclude dependencies that could cause conflicts and
+compatibility issues with other frameworks such as Spark. `hudi-utilities-slim-bundle` is to work with a chosen Spark
+bundle:
+
+- `hudi-utilities-slim-bundle` works with Spark 3.1 and 2.4.
+- `hudi-utilities-bundle` continues to work with Spark 3.1 as it does in Hudi 0.10.x.
+
+### Flink Integration Improvements
+
+- In 0.11.0, both Flink 1.13.x and 1.14.x are supported.
+- Complex data types such as `Map` and `Array` are supported. Complex data types can be nested in another component data
+  type.
+- A DFS-based Flink catalog is added with catalog identifier as `hudi`. You can instantiate the catalog through API
+  directly or use the `CREATE CATALOG` syntax to create it.
+- Flink supports [Bucket Index](#bucket-index) in normal `UPSERT` and `BULK_INSERT` operations. Different from the
+  default Flink state-based index, bucket index is in constant number of buckets. Specify SQL option `index.type`
+  as `BUCKET` to enable it.
+
+### Google BigQuery Integration
+
+In 0.11.0, Hudi tables can be queried from BigQuery as external tables. Users can
+set `org.apache.hudi.gcp.bigquery.BigQuerySyncTool` as the sync tool implementation for `HoodieDeltaStreamer` and make
+the target Hudi table discoverable in BigQuery. Please refer to the [BigQuery integration](/docs/gcp_bigquery) guide
+page for more details.
+
+*Note: this is an experimental feature and only works with hive-style partitioned Copy-On-Write tables.*
+
+### AWS Glue Meta Sync
+
+In 0.11.0, Hudi tables can be sync'ed to AWS Glue Data Catalog via AWS SDK directly. Users can
+set `org.apache.hudi.aws.sync.AwsGlueCatalogSyncTool` as the sync tool implementation for `HoodieDeltaStreamer` and make
+the target Hudi table discoverable in Glue catalog. Please refer
+to [Sync to AWS Glue Data Catalog](/docs/syncing_aws_glue_data_catalog) guide page for more details.
+
+*Note: this is an experimental feature.*
+
+### DataHub Meta Sync
+
+In 0.11.0, Hudi table's metadata (specifically, schema and last sync commit time) can be sync'ed
+to [DataHub](https://datahubproject.io/). Users can set `org.apache.hudi.sync.datahub.DataHubSyncTool` as the sync tool
+implementation for `HoodieDeltaStreamer` and sync the target table as a Dataset in DataHub. Please refer
+to [Sync to DataHub](/docs/syncing_datahub) guide page for more details.
+
+*Note: this is an experimental feature.*
+
+### Encryption
+
+In 0.11.0, Spark 3.2 support has been added and accompanying that, Parquet 1.12 has been included, which brings
+encryption feature to Hudi (Copy-on-Write tables). Please refer to [Encryption](/docs/encryption) guide page for more
+details.
+
+### Bucket Index
+
+Bucket index, an efficient and light-weight index type, is added in 0.11.0. It distributes records to buckets using a
+hash function based on the record keys, where each bucket corresponds to a single file group. To use this index, set the
+index type to `BUCKET` and set `hoodie.storage.layout.partitioner.class` to `org.apache.hudi.table.action.commit.SparkBucketIndexPartitioner`.
+For Flink, set `index.type=BUCKET`.
+
+*For more details, please refer to hoodie.bucket.index.\* in the [configurations page](/docs/configurations).*
+
+### Savepoint & Restore
+
+Disaster recovery is a mission critical feature in any production deployment. Especially when it comes to systems that
+store data. Hudi had savepoint and restore functionality right from the beginning for COW tables. In 0.11.0, we have
+added support for MOR tables.
+
+*More info about this feature can be found in [Disaster Recovery](/docs/disaster_recovery).*
+
+### Pulsar Write Commit Callback
+
+Hudi users can use `org.apache.hudi.callback.HoodieWriteCommitCallback` to invoke callback function upon successful
+commits. In 0.11.0, we add `HoodieWriteCommitPulsarCallback` in addition to the existing HTTP callback and Kafka
+callback. Please refer to the [configurations page](/docs/configurations#Write-commit-pulsar-callback-configs) for
+detailed settings.
+
+### HiveSchemaProvider
+
+In 0.11.0, `org.apache.hudi.utilities.schema.HiveSchemaProvider` is added for getting schema from user-defined hive
+tables. This is useful when tailing Hive tables in `HoodieDeltaStreamer` instead of having to provide avro schema files.
+
+## Known Regression
+
+In 0.11.0 release, with the newly added support for Spark SQL features, the following performance regressions were
+inadvertently introduced:
+* Partition pruning for some of the COW tables is not applied properly
+* Spark SQL query caching (which caches parsed and resolved queries) was not working correctly resulting in additional
+* overhead to re-analyze the query every time when it's executed (listing the table contents, etc.)
+
+All of these issues have been addressed in 0.11.1 and are validated to be resolved by benchmarking the set of changes
+on TPC-DS against 0.10.1.
+
+## Raw Release Notes
+
+The raw release notes are available [here](https://issues.apache.org/jira/secure/ReleaseNote.jspa?projectId=12322822&version=12350673)