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The following commit(s) were added to refs/heads/asf-site by this push:
new e98467e80b41 docs: fix broken and outdated links across docs (#19038)
e98467e80b41 is described below
commit e98467e80b419e041ae6ab8272143c7db74f228f
Author: deepakpanda93 <[email protected]>
AuthorDate: Fri Jun 19 07:54:04 2026 +0530
docs: fix broken and outdated links across docs (#19038)
---
website/docs/compaction.md | 2 +-
website/docs/comparison.md | 2 +-
website/docs/s3_hoodie.md | 2 +-
website/docs/sql_queries.md | 2 +-
website/docs/troubleshooting.md | 2 +-
website/versioned_docs/version-0.15.0/comparison.md | 2 +-
website/versioned_docs/version-0.15.0/troubleshooting.md | 2 +-
website/versioned_docs/version-0.15.1/comparison.md | 2 +-
website/versioned_docs/version-0.15.1/troubleshooting.md | 2 +-
website/versioned_docs/version-1.0.0/comparison.md | 2 +-
website/versioned_docs/version-1.0.0/troubleshooting.md | 2 +-
website/versioned_docs/version-1.0.1/comparison.md | 2 +-
website/versioned_docs/version-1.0.1/troubleshooting.md | 2 +-
website/versioned_docs/version-1.0.2/comparison.md | 2 +-
website/versioned_docs/version-1.0.2/troubleshooting.md | 2 +-
website/versioned_docs/version-1.1.1/compaction.md | 2 +-
website/versioned_docs/version-1.1.1/comparison.md | 2 +-
website/versioned_docs/version-1.1.1/s3_hoodie.md | 2 +-
website/versioned_docs/version-1.1.1/sql_queries.md | 2 +-
website/versioned_docs/version-1.1.1/troubleshooting.md | 2 +-
website/versioned_docs/version-1.2.0/compaction.md | 2 +-
website/versioned_docs/version-1.2.0/comparison.md | 2 +-
website/versioned_docs/version-1.2.0/s3_hoodie.md | 2 +-
website/versioned_docs/version-1.2.0/sql_queries.md | 2 +-
website/versioned_docs/version-1.2.0/troubleshooting.md | 2 +-
25 files changed, 25 insertions(+), 25 deletions(-)
diff --git a/website/docs/compaction.md b/website/docs/compaction.md
index bf1dee7c12d6..8f37c464a5bc 100644
--- a/website/docs/compaction.md
+++ b/website/docs/compaction.md
@@ -15,7 +15,7 @@ not applicable to Copy-on-Write (COW) tables and only applies
to MOR tables.
### Why MOR tables need compaction?
To understand the significance of compaction in MOR tables, it is helpful to
understand the MOR table layout first. In Hudi,
-data is organized in terms of [file
groups](https://hudi.apache.org/docs/file_layouts/). Each file group in a MOR
table
+data is organized in terms of [file
groups](https://hudi.apache.org/docs/storage_layouts/). Each file group in a
MOR table
consists of a base file and one or more log files. Typically, during writes,
inserts are stored in the base file, and updates
are appended to log files.
diff --git a/website/docs/comparison.md b/website/docs/comparison.md
index 3d2ef46a77e6..dc19c15ab1d1 100644
--- a/website/docs/comparison.md
+++ b/website/docs/comparison.md
@@ -50,5 +50,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/docs/s3_hoodie.md b/website/docs/s3_hoodie.md
index 37f79ae75342..d2151fe19e91 100644
--- a/website/docs/s3_hoodie.md
+++ b/website/docs/s3_hoodie.md
@@ -88,7 +88,7 @@ AWS glue data libraries are needed if AWS glue data is used
## AWS S3 Versioned Bucket
-With versioned buckets any object deleted creates a [Delete
Marker](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DeleteMarker.html),
as Hudi cleans up files using [Cleaner
utility](https://hudi.apache.org/docs/hoodie_cleaner) the number of Delete
Markers increases over time.
+With versioned buckets any object deleted creates a [Delete
Marker](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DeleteMarker.html),
as Hudi cleans up files using [Cleaner
utility](https://hudi.apache.org/docs/cleaning) the number of Delete Markers
increases over time.
It is important to configure the [Lifecycle
Rule](https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html)
correctly
to clean up these delete markers as the List operation can choke if the number
of delete markers reaches 1000.
We recommend cleaning up Delete Markers after 1 day in Lifecycle Rule.
\ No newline at end of file
diff --git a/website/docs/sql_queries.md b/website/docs/sql_queries.md
index 8eec17bb40d5..6737f3cdebf4 100644
--- a/website/docs/sql_queries.md
+++ b/website/docs/sql_queries.md
@@ -917,7 +917,7 @@ for more details.
## Doris
The Doris integration currently support Copy on Write and Merge On Read tables
in Hudi since version 0.10.0. You can query Hudi tables via Doris from Doris
version 2.0. Doris offers a multi-catalog, which is designed to make it easier
to connect to external data catalogs to enhance Doris's data lake analysis and
federated data query capabilities. Please refer
-to [Doris Hudi
Catalog](https://doris.apache.org/docs/lakehouse/datalake-analytics/hudi/) for
more details on the setup.
+to [Doris Hudi
Catalog](https://doris.apache.org/docs/3.x/lakehouse/catalogs/hudi-catalog) for
more details on the setup.
:::note
The current default supported version of Hudi is 0.10.0 ~ 0.13.1, and has not
been tested in other versions. More versions will be supported in the future.
diff --git a/website/docs/troubleshooting.md b/website/docs/troubleshooting.md
index 8c2b2a6cfd85..4a064d9b1cb7 100644
--- a/website/docs/troubleshooting.md
+++ b/website/docs/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-0.15.0/comparison.md
b/website/versioned_docs/version-0.15.0/comparison.md
index 30ededd13a83..3d3530887bce 100644
--- a/website/versioned_docs/version-0.15.0/comparison.md
+++ b/website/versioned_docs/version-0.15.0/comparison.md
@@ -52,5 +52,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-0.15.0/troubleshooting.md
b/website/versioned_docs/version-0.15.0/troubleshooting.md
index 6756033995b4..19c3795c417a 100644
--- a/website/versioned_docs/version-0.15.0/troubleshooting.md
+++ b/website/versioned_docs/version-0.15.0/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-0.15.1/comparison.md
b/website/versioned_docs/version-0.15.1/comparison.md
index 30ededd13a83..3d3530887bce 100644
--- a/website/versioned_docs/version-0.15.1/comparison.md
+++ b/website/versioned_docs/version-0.15.1/comparison.md
@@ -52,5 +52,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-0.15.1/troubleshooting.md
b/website/versioned_docs/version-0.15.1/troubleshooting.md
index 6756033995b4..19c3795c417a 100644
--- a/website/versioned_docs/version-0.15.1/troubleshooting.md
+++ b/website/versioned_docs/version-0.15.1/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-1.0.0/comparison.md
b/website/versioned_docs/version-1.0.0/comparison.md
index 30ededd13a83..3d3530887bce 100644
--- a/website/versioned_docs/version-1.0.0/comparison.md
+++ b/website/versioned_docs/version-1.0.0/comparison.md
@@ -52,5 +52,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-1.0.0/troubleshooting.md
b/website/versioned_docs/version-1.0.0/troubleshooting.md
index 47de1002beae..14e7df400aac 100644
--- a/website/versioned_docs/version-1.0.0/troubleshooting.md
+++ b/website/versioned_docs/version-1.0.0/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-1.0.1/comparison.md
b/website/versioned_docs/version-1.0.1/comparison.md
index 30ededd13a83..3d3530887bce 100644
--- a/website/versioned_docs/version-1.0.1/comparison.md
+++ b/website/versioned_docs/version-1.0.1/comparison.md
@@ -52,5 +52,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-1.0.1/troubleshooting.md
b/website/versioned_docs/version-1.0.1/troubleshooting.md
index 47de1002beae..14e7df400aac 100644
--- a/website/versioned_docs/version-1.0.1/troubleshooting.md
+++ b/website/versioned_docs/version-1.0.1/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-1.0.2/comparison.md
b/website/versioned_docs/version-1.0.2/comparison.md
index 30ededd13a83..3d3530887bce 100644
--- a/website/versioned_docs/version-1.0.2/comparison.md
+++ b/website/versioned_docs/version-1.0.2/comparison.md
@@ -52,5 +52,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-1.0.2/troubleshooting.md
b/website/versioned_docs/version-1.0.2/troubleshooting.md
index 8c2961327885..53143ce2118b 100644
--- a/website/versioned_docs/version-1.0.2/troubleshooting.md
+++ b/website/versioned_docs/version-1.0.2/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-1.1.1/compaction.md
b/website/versioned_docs/version-1.1.1/compaction.md
index 55aae1f4697f..3a3fd88bc8c2 100644
--- a/website/versioned_docs/version-1.1.1/compaction.md
+++ b/website/versioned_docs/version-1.1.1/compaction.md
@@ -15,7 +15,7 @@ not applicable to Copy-on-Write (COW) tables and only applies
to MOR tables.
### Why MOR tables need compaction?
To understand the significance of compaction in MOR tables, it is helpful to
understand the MOR table layout first. In Hudi,
-data is organized in terms of [file
groups](https://hudi.apache.org/docs/file_layouts/). Each file group in a MOR
table
+data is organized in terms of [file
groups](https://hudi.apache.org/docs/storage_layouts/). Each file group in a
MOR table
consists of a base file and one or more log files. Typically, during writes,
inserts are stored in the base file, and updates
are appended to log files.
diff --git a/website/versioned_docs/version-1.1.1/comparison.md
b/website/versioned_docs/version-1.1.1/comparison.md
index 3d2ef46a77e6..dc19c15ab1d1 100644
--- a/website/versioned_docs/version-1.1.1/comparison.md
+++ b/website/versioned_docs/version-1.1.1/comparison.md
@@ -50,5 +50,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-1.1.1/s3_hoodie.md
b/website/versioned_docs/version-1.1.1/s3_hoodie.md
index 37f79ae75342..d2151fe19e91 100644
--- a/website/versioned_docs/version-1.1.1/s3_hoodie.md
+++ b/website/versioned_docs/version-1.1.1/s3_hoodie.md
@@ -88,7 +88,7 @@ AWS glue data libraries are needed if AWS glue data is used
## AWS S3 Versioned Bucket
-With versioned buckets any object deleted creates a [Delete
Marker](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DeleteMarker.html),
as Hudi cleans up files using [Cleaner
utility](https://hudi.apache.org/docs/hoodie_cleaner) the number of Delete
Markers increases over time.
+With versioned buckets any object deleted creates a [Delete
Marker](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DeleteMarker.html),
as Hudi cleans up files using [Cleaner
utility](https://hudi.apache.org/docs/cleaning) the number of Delete Markers
increases over time.
It is important to configure the [Lifecycle
Rule](https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html)
correctly
to clean up these delete markers as the List operation can choke if the number
of delete markers reaches 1000.
We recommend cleaning up Delete Markers after 1 day in Lifecycle Rule.
\ No newline at end of file
diff --git a/website/versioned_docs/version-1.1.1/sql_queries.md
b/website/versioned_docs/version-1.1.1/sql_queries.md
index 81ce6f0b49a2..61812b200093 100644
--- a/website/versioned_docs/version-1.1.1/sql_queries.md
+++ b/website/versioned_docs/version-1.1.1/sql_queries.md
@@ -709,7 +709,7 @@ for more details.
## Doris
The Doris integration currently support Copy on Write and Merge On Read tables
in Hudi since version 0.10.0. You can query Hudi tables via Doris from Doris
version 2.0. Doris offers a multi-catalog, which is designed to make it easier
to connect to external data catalogs to enhance Doris's data lake analysis and
federated data query capabilities. Please refer
-to [Doris Hudi
Catalog](https://doris.apache.org/docs/lakehouse/datalake-analytics/hudi/) for
more details on the setup.
+to [Doris Hudi
Catalog](https://doris.apache.org/docs/3.x/lakehouse/catalogs/hudi-catalog) for
more details on the setup.
:::note
The current default supported version of Hudi is 0.10.0 ~ 0.13.1, and has not
been tested in other versions. More versions will be supported in the future.
diff --git a/website/versioned_docs/version-1.1.1/troubleshooting.md
b/website/versioned_docs/version-1.1.1/troubleshooting.md
index 8c2b2a6cfd85..4a064d9b1cb7 100644
--- a/website/versioned_docs/version-1.1.1/troubleshooting.md
+++ b/website/versioned_docs/version-1.1.1/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
diff --git a/website/versioned_docs/version-1.2.0/compaction.md
b/website/versioned_docs/version-1.2.0/compaction.md
index bf6a5689feb5..ada7a66e0ced 100644
--- a/website/versioned_docs/version-1.2.0/compaction.md
+++ b/website/versioned_docs/version-1.2.0/compaction.md
@@ -15,7 +15,7 @@ not applicable to Copy-on-Write (COW) tables and only applies
to MOR tables.
### Why MOR tables need compaction?
To understand the significance of compaction in MOR tables, it is helpful to
understand the MOR table layout first. In Hudi,
-data is organized in terms of [file
groups](https://hudi.apache.org/docs/file_layouts/). Each file group in a MOR
table
+data is organized in terms of [file
groups](https://hudi.apache.org/docs/storage_layouts/). Each file group in a
MOR table
consists of a base file and one or more log files. Typically, during writes,
inserts are stored in the base file, and updates
are appended to log files.
diff --git a/website/versioned_docs/version-1.2.0/comparison.md
b/website/versioned_docs/version-1.2.0/comparison.md
index 3d2ef46a77e6..dc19c15ab1d1 100644
--- a/website/versioned_docs/version-1.2.0/comparison.md
+++ b/website/versioned_docs/version-1.2.0/comparison.md
@@ -50,5 +50,5 @@ of PrestoDB/SparkSQL/Hive for your queries.
More advanced use cases revolve around the concepts of [incremental
processing](https://www.oreilly.com/ideas/ubers-case-for-incremental-processing-on-hadoop),
which effectively
uses Hudi even inside the `processing` engine to speed up typical batch
pipelines. For e.g: Hudi can be used as a state store inside a processing DAG
(similar
-to how
[rocksDB](https://ci.apache.org/projects/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
+to how
[rocksDB](https://nightlies.apache.org/flink/flink-docs-release-1.2/ops/state_backends.html#the-rocksdbstatebackend)
is used by Flink). This is an item on the roadmap
and will eventually happen as a [Beam
Runner](https://github.com/apache/hudi/issues/14452)
diff --git a/website/versioned_docs/version-1.2.0/s3_hoodie.md
b/website/versioned_docs/version-1.2.0/s3_hoodie.md
index 37f79ae75342..d2151fe19e91 100644
--- a/website/versioned_docs/version-1.2.0/s3_hoodie.md
+++ b/website/versioned_docs/version-1.2.0/s3_hoodie.md
@@ -88,7 +88,7 @@ AWS glue data libraries are needed if AWS glue data is used
## AWS S3 Versioned Bucket
-With versioned buckets any object deleted creates a [Delete
Marker](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DeleteMarker.html),
as Hudi cleans up files using [Cleaner
utility](https://hudi.apache.org/docs/hoodie_cleaner) the number of Delete
Markers increases over time.
+With versioned buckets any object deleted creates a [Delete
Marker](https://docs.aws.amazon.com/AmazonS3/latest/userguide/DeleteMarker.html),
as Hudi cleans up files using [Cleaner
utility](https://hudi.apache.org/docs/cleaning) the number of Delete Markers
increases over time.
It is important to configure the [Lifecycle
Rule](https://docs.aws.amazon.com/AmazonS3/latest/userguide/object-lifecycle-mgmt.html)
correctly
to clean up these delete markers as the List operation can choke if the number
of delete markers reaches 1000.
We recommend cleaning up Delete Markers after 1 day in Lifecycle Rule.
\ No newline at end of file
diff --git a/website/versioned_docs/version-1.2.0/sql_queries.md
b/website/versioned_docs/version-1.2.0/sql_queries.md
index 71d71812c7b0..593a0bad7f5b 100644
--- a/website/versioned_docs/version-1.2.0/sql_queries.md
+++ b/website/versioned_docs/version-1.2.0/sql_queries.md
@@ -913,7 +913,7 @@ for more details.
## Doris
The Doris integration currently support Copy on Write and Merge On Read tables
in Hudi since version 0.10.0. You can query Hudi tables via Doris from Doris
version 2.0. Doris offers a multi-catalog, which is designed to make it easier
to connect to external data catalogs to enhance Doris's data lake analysis and
federated data query capabilities. Please refer
-to [Doris Hudi
Catalog](https://doris.apache.org/docs/lakehouse/datalake-analytics/hudi/) for
more details on the setup.
+to [Doris Hudi
Catalog](https://doris.apache.org/docs/3.x/lakehouse/catalogs/hudi-catalog) for
more details on the setup.
:::note
The current default supported version of Hudi is 0.10.0 ~ 0.13.1, and has not
been tested in other versions. More versions will be supported in the future.
diff --git a/website/versioned_docs/version-1.2.0/troubleshooting.md
b/website/versioned_docs/version-1.2.0/troubleshooting.md
index 8c2b2a6cfd85..4a064d9b1cb7 100644
--- a/website/versioned_docs/version-1.2.0/troubleshooting.md
+++ b/website/versioned_docs/version-1.2.0/troubleshooting.md
@@ -137,7 +137,7 @@ First of all, please confirm if you do indeed have
duplicates **AFTER** ensuring
### Ingestion
-#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at
[kafka.utils.Utils$.read](http://kafka.utils.Utils$.read)(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
+#### java.io.EOFException: Received -1 when reading from channel, socket has
likely been closed. at `kafka.utils.Utils$.read`(Utils.scala:381) at
kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
This might happen if you are ingesting from Kafka source, your cluster is ssl
enabled by default and you are using some version of Hudi older than 0.5.1.
Previous versions of Hudi were using spark-streaming-kafka-0-8 library. With
the release of 0.5.1 version of Hudi, spark was upgraded to 2.4.4 and
spark-streaming-kafka library was upgraded to spark-streaming-kafka-0-10. SSL
support was introduced from spark-streaming-kafka-0-10. Please see here for
reference.
