This is an automated email from the ASF dual-hosted git repository.
jeffreyh pushed a commit to branch master
in repository https://gitbox.apache.org/repos/asf/doris-website.git
The following commit(s) were added to refs/heads/master by this push:
new e351842dd19 feat:redirect to slack (#3267)
e351842dd19 is described below
commit e351842dd19dd4ab01a160c2f6ee54b82ef477cc
Author: yangon <[email protected]>
AuthorDate: Wed Jan 7 21:29:25 2026 +0800
feat:redirect to slack (#3267)
---
...o-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md | 2 +-
...lytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md | 2 +-
blog/Building-a-Data-Warehouse-for-Traditional-Industry.md | 2 +-
blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md | 2 +-
blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md | 2 +-
...h-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md | 2 +-
...ata-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md | 2 +-
...lly-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md | 2 +-
blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md | 2 +-
...st-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md | 2 +-
...cing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md | 2 +-
blog/Say-Goodbye-to-OOM-Crashes.md | 2 +-
...cent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md | 2 +-
blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md | 2 +-
blog/Understanding-Data-Compaction-in-3-Minutes.md | 2 +-
...e-high-available-real-time-data-warehouse-based-on-apache-doris.md | 2 +-
...al-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md | 2 +-
...inimax-from-loki-and-built-a-pb-scale-logging-system-with-doris.md | 2 +-
blog/apache-doris-for-log-and-time-series-data-analysis-in-netease.md | 4 ++--
...-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md | 2 +-
...-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md | 2 +-
blog/arrow-flight-sql-in-apache-doris-for-10x-faster-data-transfer.md | 2 +-
blog/auto-increment-columns-in-databases.md | 2 +-
blog/auto-partition-in-apache-doris.md | 2 +-
blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md | 2 +-
blog/cross-cluster-replication-for-read-write.md | 2 +-
...ve-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md | 2 +-
...ring-cyber-security-by-enabling-seven-times-faster-log-analysis.md | 2 +-
blog/evolution-of-the-apache-doris-execution-engine.md | 2 +-
...asticsearch-to-apache-doris-upgrading-an-observability-platform.md | 4 ++--
...house-and-hive-to-apache-doris-sql-convertor-for-easy-migration.md | 2 +-
...g-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md | 2 +-
...tion-to-apache-doris-a-next-generation-real-time-data-warehouse.md | 2 +-
...nverted-index-accelerates-text-searches-by-40-time-apache-doris.md | 2 +-
blog/job-scheduler-for-task-automation.md | 2 +-
blog/log-analysis-elasticsearch-vs-apache-doris.md | 2 +-
blog/migrate-lakehouse-from-bigquery-to-doris.md | 4 ++--
blog/migrating-from-clickhouse-to-apache-doris-what-happened.md | 2 +-
blog/multi-tenant-workload-isolation-in-apache-doris.md | 2 +-
blog/release-note-2.0.0.md | 2 +-
blog/release-note-2.1.0.md | 2 +-
blog/release-note-3.0.0.md | 2 +-
blog/tencent-music-migrate-elasticsearch-to-doris.md | 2 +-
blog/variant-in-apache-doris-2.1.md | 2 +-
blog/why-apache-doris-is-best-alternatives-for-real-time-analytics.md | 2 +-
community/how-to-contribute/contribute-to-doris.md | 2 +-
community/join-community.md | 2 +-
docs/releasenotes/v3.0/release-3.0.0.md | 2 +-
docusaurus.config.js | 4 ++++
.../current/how-to-contribute/contribute-to-doris.md | 2 +-
.../current/join-community.md | 2 +-
src/pages/index.tsx | 4 ++--
src/theme/Footer/index.tsx | 2 +-
src/theme/Navbar/Content/components/NavbarCommon.tsx | 2 +-
src/theme/TOC/index.tsx | 2 +-
versioned_docs/version-2.1/releasenotes/v3.0/release-3.0.0.md | 2 +-
versioned_docs/version-3.x/releasenotes/v3.0/release-3.0.0.md | 2 +-
versioned_docs/version-4.x/releasenotes/v3.0/release-3.0.0.md | 2 +-
58 files changed, 65 insertions(+), 61 deletions(-)
diff --git
a/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
b/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
index 94e06e4d631..b9be94dcfb8 100644
--- a/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
+++ b/blog/Auto-Synchronization-of-an-Entire-MySQL-Database-for-Data-Analysis.md
@@ -191,5 +191,5 @@ CREATE TABLE doris_sink (
);
```
-If you've got any questions, find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+If you've got any questions, find Apache Doris developers on
[Slack](https://doris.apache.org/slack).
diff --git
a/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
b/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
index 256ac9bbf8d..208af91b3d7 100644
---
a/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
+++
b/blog/Building-A-Log-Analytics-Solution-10-Times-More-Cost-Effective-Than-Elasticsearch.md
@@ -247,4 +247,4 @@ For more feature introduction and usage guide, see
documentation: [Inverted Inde
In a word, what contributes to Apache Doris' 10-time higher cost-effectiveness
than Elasticsearch is its OLAP-tailored optimizations for inverted indexing,
supported by the columnar storage engine, massively parallel processing
framework, vectorized query engine, and cost-based optimizer of Apache Doris.
-As proud as we are about our own inverted indexing solution, we understand
that self-published benchmarks can be controversial, so we are open to
[feedback](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
from any third-party users and see how [Apache
Doris](https://github.com/apache/doris) works in real-world cases.
+As proud as we are about our own inverted indexing solution, we understand
that self-published benchmarks can be controversial, so we are open to
[feedback](https://doris.apache.org/slack) from any third-party users and see
how [Apache Doris](https://github.com/apache/doris) works in real-world cases.
diff --git a/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
b/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
index 7eff20ccb4f..d019c168b60 100644
--- a/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
+++ b/blog/Building-a-Data-Warehouse-for-Traditional-Industry.md
@@ -172,4 +172,4 @@ Actually, before we evolved into our current data
architecture, we tried Hive, S
On the other hand, to smoothen our big data transition, we need to make our
data platform as simple as possible in terms of usage and maintenance. That's
why we landed on Apache Doris. It is compatible with MySQL protocol and
provides a rich collection of functions so we don't have to develop our own
UDFs. Also, it is composed of only two types of processes: frontends and
backends, so it is easy to scale and track.
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+Find Apache Doris developers on [Slack](https://doris.apache.org/slack).
diff --git
a/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
b/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
index 5663da2f13e..67beab10718 100644
--- a/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
+++ b/blog/Building-the-Next-Generation-Data-Lakehouse-10X-Performance.md
@@ -249,5 +249,5 @@ http://doris.apache.org
https://github.com/apache/doris
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+Find Apache Doris developers on [Slack](https://doris.apache.org/slack).
diff --git a/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
b/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
index 9d31f8037aa..38a5b69dc18 100644
--- a/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
+++ b/blog/Database-Dissection-How-Fast-Data-Queries-Are-Implemented.md
@@ -134,7 +134,7 @@ The results are as below:
In short, what contributed to the fast data loading and data queries in this
case?
- The Colocate mechanism that's designed for distributed computing
-- Collaboration between database users and
[developers](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
that enables the operator merging
+- Collaboration between database users and
[developers](https://doris.apache.org/slack) that enables the operator merging
- Support for a wide range of data loading methods to choose from
- A vectorized engine that brings overall performance increase
diff --git
a/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
b/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
index d64048d44c3..0d81adde3b5 100644
---
a/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
+++
b/blog/Database-in-Fintech-How-to-Support-ten-thousand-Dashboards-Without-Causing-a-Mess.md
@@ -73,7 +73,7 @@ Analysts often check data reports of the same metrics on a
regular basis. These
The complexity of data analysis in the financial industry lies in the data
itself other than the engineering side. Thus, the underlying data architecture
should focus on facilitating the unified and efficient management of data.
Apache Doris provides the flexibility of simple metric registration and the
ability of fast and resource-efficient metric computation. In this case, the
user is able to handle 10,000 active financial metrics in 10,000 dashboards
with 30% less ETL efforts.
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+Find Apache Doris developers on [Slack](https://doris.apache.org/slack).
diff --git
a/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
b/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
index 0619a1f0a6c..24ed3dbe120 100644
---
a/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
+++
b/blog/For-Entry-Level-Data-Engineers-How-to-Build-a-Simple-but-Solid-Data-Architecture.md
@@ -100,4 +100,4 @@ Firstly, Apache Doris is famously fast in Join queries. So
if you need to extrac
## Conclusion
-This is the overview of a simple data architecture and how it can provide the
data services you need. It ensures data ingestion stability and quality with
Flink CDC, and quick data analysis with Apache Doris. The deployment of this
architecture is simple, too. If you plan for a data analytic upgrade for your
business, you might refer to this case. If you need advice and help, you may
join our [community
here](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4
[...]
+This is the overview of a simple data architecture and how it can provide the
data services you need. It ensures data ingestion stability and quality with
Flink CDC, and quick data analysis with Apache Doris. The deployment of this
architecture is simple, too. If you plan for a data analytic upgrade for your
business, you might refer to this case. If you need advice and help, you may
join our [community here](https://doris.apache.org/slack).
diff --git
a/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
b/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
index 1897fef3b97..608482a4275 100644
---
a/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
+++
b/blog/Is-Your-Latest-Data-Really-the-Latest-Check-the-Data-Update-Mechanism-of-Your-Database.md
@@ -223,5 +223,5 @@ mysql> select * from test_table;
## Conclusion
-Congratulations. Now you've gained an overview of how data updates are
implemented in Apache Doris. With this knowledge, you can basically guarantee
efficiency and accuracy of data updating. But wait, there is so much more about
that. As Apache Doris 2.0 is going to provide more powerful Partial Column
Update capabilities, with improved execution of the Update statement and the
support for more complicated multi-table Join queries, I will show you how to
take advantage of them in details [...]
+Congratulations. Now you've gained an overview of how data updates are
implemented in Apache Doris. With this knowledge, you can basically guarantee
efficiency and accuracy of data updating. But wait, there is so much more about
that. As Apache Doris 2.0 is going to provide more powerful Partial Column
Update capabilities, with improved execution of the Update statement and the
support for more complicated multi-table Join queries, I will show you how to
take advantage of them in details [...]
diff --git a/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
b/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
index 994a2765f8d..641201f8aeb 100644
--- a/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
+++ b/blog/Listen-to-That-Poor-BI-Engineer-We-Need-Fast-Joins.md
@@ -102,4 +102,4 @@ We believe self-service BI is the future in the BI
landscape, just like AGI is t
-Find the Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
+Find the Apache Doris developers on [Slack](https://doris.apache.org/slack)
diff --git
a/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
b/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
index 5ad31859c1d..3a03e0b787a 100644
---
a/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
+++
b/blog/Log-Analysis-How-to-Digest-15-Billion-Logs-Per-Day-and-Keep-Big-Queries-Within-1-Second.md
@@ -88,7 +88,7 @@ These strategies have shortened the response time of queries.
For example, a que
## Ongoing Plans
-The user is now testing with the newly added [inverted
index](https://doris.apache.org/docs/table-design/index/inverted-index) in
Apache Doris. It is designed to speed up full-text search of strings as well as
equivalence and range queries of numerics and datetime. They have also provided
their valuable feedback about the auto-bucketing logic in Doris: Currently,
Doris decides the number of buckets for a partition based on the data size of
the previous partition. The problem for the use [...]
+The user is now testing with the newly added [inverted
index](https://doris.apache.org/docs/table-design/index/inverted-index) in
Apache Doris. It is designed to speed up full-text search of strings as well as
equivalence and range queries of numerics and datetime. They have also provided
their valuable feedback about the auto-bucketing logic in Doris: Currently,
Doris decides the number of buckets for a partition based on the data size of
the previous partition. The problem for the use [...]
diff --git
a/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
b/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
index 437b4629e52..a759bdad044 100644
---
a/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
+++
b/blog/Replacing-Apache-Hive-Elasticsearch-and-PostgreSQL-with-Apache-Doris.md
@@ -114,7 +114,7 @@ We have 2 clusters in Apache Doris accommodating tens of
TBs of data, with almos
-Lastly, I would like to share with you something that interested us most when
we first talked to the [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw):
+Lastly, I would like to share with you something that interested us most when
we first talked to the [Apache Doris community](https://doris.apache.org/slack):
- Apache Doris supports data ingestion transactions so it can ensure data is
written **exactly once**.
- It is well-integrated with the data ecosystem and can smoothly interface
with most data sources and data formats.
diff --git a/blog/Say-Goodbye-to-OOM-Crashes.md
b/blog/Say-Goodbye-to-OOM-Crashes.md
index ee7fbc94191..86c28480d6a 100644
--- a/blog/Say-Goodbye-to-OOM-Crashes.md
+++ b/blog/Say-Goodbye-to-OOM-Crashes.md
@@ -163,5 +163,5 @@ If the process memory consumed is beyond the MemLimit (90%
of total system memor
After optimizations in memory allocation, memory tracking, and memory limit,
we have substantially increased the stability and high-concurrency performance
of Apache Doris as a real-time analytic data warehouse platform. OOM crash in
the backend is a rare scene now. Even if there is an OOM, users can locate the
problem root based on the logs and then fix it. In addition, with more flexible
memory limits on queries and data ingestion, users don't have to spend extra
effort taking care of [...]
-In the next phase, we plan to ensure completion of queries in memory
overcommitment, which means less queries will have to be canceled due to memory
shortage. We have broken this objective into specific directions of work:
exception safety, memory isolation between resource groups, and the flushing
mechanism of intermediate data. If you want to meet our developers, [this is
where you find
us](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+In the next phase, we plan to ensure completion of queries in memory
overcommitment, which means less queries will have to be canceled due to memory
shortage. We have broken this objective into specific directions of work:
exception safety, memory isolation between resource groups, and the flushing
mechanism of intermediate data. If you want to meet our developers, [this is
where you find us](https://doris.apache.org/slack).
diff --git
a/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
b/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
index 645c62d26bd..be4cbba171a 100644
--- a/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
+++ b/blog/Tencent-Data-Engineers-Why-We-Went-from-ClickHouse-to-Apache-Doris.md
@@ -255,4 +255,4 @@ http://doris.apache.org
https://github.com/apache/doris
-Find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
+Find Apache Doris developers on [Slack](https://doris.apache.org/slack)
diff --git a/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
b/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
index 1a6c99f0aac..c4d4d8405d4 100644
--- a/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
+++ b/blog/Tiered-Storage-for-Hot-and-Cold-Data-What-Why-and-How.md
@@ -353,7 +353,7 @@ Apache Doris 2.0 has been optimized for cold data queries.
Only the first-time a
In Apache Doris, each data ingestion leads to the generation of a new Rowset,
so the update of historical data will be put in a Rowset that is separated from
those of newly loaded data. That’s how it makes sure the updating of cold data
does not interfere with the ingestion of hot data. Once the rowsets cool down,
they will be moved to S3 and deleted locally, and the updated historical data
will go to the partition where it belongs.
-If you any questions, come find Apache Doris developers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
We will be happy to provide targeted support.
+If you any questions, come find Apache Doris developers on
[Slack](https://doris.apache.org/slack). We will be happy to provide targeted
support.
diff --git a/blog/Understanding-Data-Compaction-in-3-Minutes.md
b/blog/Understanding-Data-Compaction-in-3-Minutes.md
index 91b24555998..488d95f716b 100644
--- a/blog/Understanding-Data-Compaction-in-3-Minutes.md
+++ b/blog/Understanding-Data-Compaction-in-3-Minutes.md
@@ -128,4 +128,4 @@ Every data engineer has somehow been harassed by
complicated parameters and conf
## Conclusion
-This is how we keep our "storekeepers" working efficiently and
cost-effectively. If you wonder how these strategies and optimization work in
real practice, we tested Apache Doris with ClickBench. It reaches a
**compaction speed of 300,000 row/s**; in high-concurrency scenarios, it
maintains **a stable compaction score of around 50**. Also, we are planning to
implement auto-tuning and increase observability for the compaction mechanism.
If you are interested in the [Apache Doris](https:// [...]
+This is how we keep our "storekeepers" working efficiently and
cost-effectively. If you wonder how these strategies and optimization work in
real practice, we tested Apache Doris with ClickBench. It reaches a
**compaction speed of 300,000 row/s**; in high-concurrency scenarios, it
maintains **a stable compaction score of around 50**. Also, we are planning to
implement auto-tuning and increase observability for the compaction mechanism.
If you are interested in the [Apache Doris](https:// [...]
diff --git
a/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
b/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
index fb99a85e706..dea87b206a9 100644
---
a/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
+++
b/blog/a-fast-secure-high-available-real-time-data-warehouse-based-on-apache-doris.md
@@ -147,4 +147,4 @@ Disaster recovery is crucial for the financial industry.
The user leverages the
## Conclusion
-We appreciate the user for their active
[communication](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
with us along the way and are glad to see so many Apache Doris features fit in
their needs. They are also planning on exploring federated query,
compute-storage separation, and auto maintenance with Apache Doris. We look
forward to more best practice and feedback from them.
\ No newline at end of file
+We appreciate the user for their active
[communication](https://doris.apache.org/slack) with us along the way and are
glad to see so many Apache Doris features fit in their needs. They are also
planning on exploring federated query, compute-storage separation, and auto
maintenance with Apache Doris. We look forward to more best practice and
feedback from them.
\ No newline at end of file
diff --git
a/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
b/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
index 6d9eff38a63..d3af7ec45fc 100644
---
a/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
+++
b/blog/a-financial-anti-fraud-solution-based-on-the-apache-doris-data-warehouse.md
@@ -105,4 +105,4 @@ So far, the bank has added nearly 100 alerting rules for
various risk types to t
## Conclusion
-For a comprehensive anti-fraud solution, the bank conducts full-scale
real-time monitoring and reporting for all their data workflows. Then, for each
transaction, they look into the multiple dimensions of it to identify risks.
For the suspicious transactions reported by the bank customers, they perform
federated queries to retrieve the full details of them. Also, an auto alerting
mechanism is always on patrol to safeguard the whole system. These are the
various types of analytic workload [...]
\ No newline at end of file
+For a comprehensive anti-fraud solution, the bank conducts full-scale
real-time monitoring and reporting for all their data workflows. Then, for each
transaction, they look into the multiple dimensions of it to identify risks.
For the suspicious transactions reported by the bank customers, they perform
federated queries to retrieve the full details of them. Also, an auto alerting
mechanism is always on patrol to safeguard the whole system. These are the
various types of analytic workload [...]
\ No newline at end of file
diff --git
a/blog/ai-unicorn-minimax-from-loki-and-built-a-pb-scale-logging-system-with-doris.md
b/blog/ai-unicorn-minimax-from-loki-and-built-a-pb-scale-logging-system-with-doris.md
index 0768d97e945..a9d3730536d 100644
---
a/blog/ai-unicorn-minimax-from-loki-and-built-a-pb-scale-logging-system-with-doris.md
+++
b/blog/ai-unicorn-minimax-from-loki-and-built-a-pb-scale-logging-system-with-doris.md
@@ -143,4 +143,4 @@ After a successful initial experience with Apache Doris,
MiniMax proceeds with t
- **Lakehousing**: expand the use of Apache Doris include big data processing
and analysis within MiniMax, laying the foundation for a data lakehouse.
-If you have any questions or require assistance regarding Apache Doris, join
the
[community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
\ No newline at end of file
+If you have any questions or require assistance regarding Apache Doris, join
the [community](https://doris.apache.org/slack).
\ No newline at end of file
diff --git
a/blog/apache-doris-for-log-and-time-series-data-analysis-in-netease.md
b/blog/apache-doris-for-log-and-time-series-data-analysis-in-netease.md
index a1577749fb8..ce57a6ab4d9 100644
--- a/blog/apache-doris-for-log-and-time-series-data-analysis-in-netease.md
+++ b/blog/apache-doris-for-log-and-time-series-data-analysis-in-netease.md
@@ -161,7 +161,7 @@ streaming_load_json_max_mb=250
During peak times, the data platform is undertaking up to 1 million TPS and a
writing throughput of 1GB/s. This is demanding for the system. Meanwhile, at
peak time, a large number of concurrent write operations are loading data into
lots of tables, but each individual write operation only involves a small
amount of data. Thus, it takes a long time to accumulate a batch, which is
contradictory to the data freshness requirement from the query side.
-As a result, the data platform was bottlenecked by data backlogs in Apache
Kafka. NetEase adopts the [Stream
Load](https://doris.apache.org/docs/2.0/data-operate/import/stream-load-manual)
method to ingest data from Kafka to Doris. So the key was to accelerate Stream
Load. After talking to the [Apache Doris
developers](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw),
NetEase adopted two optimizations for their log and time series data analysis:
+As a result, the data platform was bottlenecked by data backlogs in Apache
Kafka. NetEase adopts the [Stream
Load](https://doris.apache.org/docs/2.0/data-operate/import/stream-load-manual)
method to ingest data from Kafka to Doris. So the key was to accelerate Stream
Load. After talking to the [Apache Doris
developers](https://doris.apache.org/slack), NetEase adopted two optimizations
for their log and time series data analysis:
- **Single replica data loading**: Load one data replica and pull data from it
to generate more replicas. This avoids the overhead of ranking and creating
indexes for multiple replicas.
@@ -234,4 +234,4 @@ If you want to enable `support_phrase` for existing tables
that have already bee
## Conclusion
-Apache Doris supports the log and time series data analytic workloads of
NetEase with higher query performance and less storage consumption. Beyond
these, Apache Doris has other capabilities such as data lake analysis since it
is designed as an all-in-one big data analytic platform. If you want a quick
evaluation of whether Doris is right for your use case, come talk to the Doris
makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
\ No newline at end of file
+Apache Doris supports the log and time series data analytic workloads of
NetEase with higher query performance and less storage consumption. Beyond
these, Apache Doris has other capabilities such as data lake analysis since it
is designed as an all-in-one big data analytic platform. If you want a quick
evaluation of whether Doris is right for your use case, come talk to the Doris
makers on [Slack](https://doris.apache.org/slack).
\ No newline at end of file
diff --git
a/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
b/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
index f0dad739707..88a91b8a72e 100644
---
a/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
+++
b/blog/apache-doris-speeds-up-data-reporting-tagging-and-data-lake-analytics.md
@@ -90,6 +90,6 @@ For easier deployment, they have also optimized their Deploy
on Yarn process via
## Conclusion
-For data reporting and customer tagging, Apache Doris smoothens data ingestion
and merging steps, and delivers high query performance based on its own design
and functionality. For data lake analytics, the user improves resource
efficiency by elastic scaling of clusters using the Compute Node. Along their
journey with Apache Doris, they have also developed a data ingestion task
prioritizing mechanism and contributed it to the Doris project. A gesture to
facilitate their use case ends up [...]
+For data reporting and customer tagging, Apache Doris smoothens data ingestion
and merging steps, and delivers high query performance based on its own design
and functionality. For data lake analytics, the user improves resource
efficiency by elastic scaling of clusters using the Compute Node. Along their
journey with Apache Doris, they have also developed a data ingestion task
prioritizing mechanism and contributed it to the Doris project. A gesture to
facilitate their use case ends up [...]
Check Apache Doris [repo](https://github.com/apache/doris) on GitHub
\ No newline at end of file
diff --git
a/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
b/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
index d5a0924b6f0..95ec2a96f8f 100644
---
a/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
+++
b/blog/apache-doris-summit-asia-2023-what-can-you-expect-from-apache-doris-as-a-data-warehouse.md
@@ -174,4 +174,4 @@ From the self-developed pre-aggregation storage engine,
materialized views, and
- We want to keep inspiring the data world by presenting more use cases.
- We want to provide more and better choices for users by collaborating with
partners along the data pipeline and cloud service providers.
-By choosing Apache Doris, you choose to stay in the heartbeat of innovation.
The [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
awaits newcomers.
+By choosing Apache Doris, you choose to stay in the heartbeat of innovation.
The [Apache Doris community](https://doris.apache.org/slack) awaits newcomers.
diff --git
a/blog/arrow-flight-sql-in-apache-doris-for-10x-faster-data-transfer.md
b/blog/arrow-flight-sql-in-apache-doris-for-10x-faster-data-transfer.md
index 3b15e9bdbcd..c3372a8e43d 100644
--- a/blog/arrow-flight-sql-in-apache-doris-for-10x-faster-data-transfer.md
+++ b/blog/arrow-flight-sql-in-apache-doris-for-10x-faster-data-transfer.md
@@ -461,4 +461,4 @@ For Spark users, apart from connecting to Flight SQL Server
using JDBC and JAVA,
A number of enterprise users of Doris has tried loading data from Doris to
Python, Spark, and Flink using Arrow Flight SQL and enjoyed much faster data
reading speed. In the future, we plan to include the support for Arrow Flight
SQL in data writing, too. By then, most systems built with mainstream
programming languages will be able to read and write data from/to Apache Doris
by an ADBC client. That's high-speed data interaction which opens up numerous
possibilities. On our to-do list, w [...]
-Download [Apache Doris 2.1](https://doris.apache.org/download/) and get a
taste of 100 times faster data transfer powered by Arrow Flight SQL. If you
need assistance, come find us in the [Apache Doris developer and user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+Download [Apache Doris 2.1](https://doris.apache.org/download/) and get a
taste of 100 times faster data transfer powered by Arrow Flight SQL. If you
need assistance, come find us in the [Apache Doris developer and user
community](https://doris.apache.org/slack).
diff --git a/blog/auto-increment-columns-in-databases.md
b/blog/auto-increment-columns-in-databases.md
index 86ff2926afa..b0430c8f996 100644
--- a/blog/auto-increment-columns-in-databases.md
+++ b/blog/auto-increment-columns-in-databases.md
@@ -408,5 +408,5 @@ Attention is required regarding:
## Conclusion
-AUTO_INCREMENT brings higher stability and reliability for Doris in
large-scale data processing. If it sounds like something you need, download
[Apache Doris](https://doris.apache.org/download/) and try it out. For issues
you come across along the way, join us in the [Apache Doris developer and user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
and we are happy to help.
+AUTO_INCREMENT brings higher stability and reliability for Doris in
large-scale data processing. If it sounds like something you need, download
[Apache Doris](https://doris.apache.org/download/) and try it out. For issues
you come across along the way, join us in the [Apache Doris developer and user
community](https://doris.apache.org/slack) and we are happy to help.
diff --git a/blog/auto-partition-in-apache-doris.md
b/blog/auto-partition-in-apache-doris.md
index 49e327cb3d2..245f1e82560 100644
--- a/blog/auto-partition-in-apache-doris.md
+++ b/blog/auto-partition-in-apache-doris.md
@@ -479,4 +479,4 @@ Plans for Auto Partition by LIST:
- Allow merging multiple values into the same partition based on specific
rules.
-Join [Apache Doris open-source
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
for more information and further guidance.
\ No newline at end of file
+Join [Apache Doris open-source community](https://doris.apache.org/slack) for
more information and further guidance.
\ No newline at end of file
diff --git a/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
b/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
index 78ae49636ff..ce9d75aa1c9 100644
--- a/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
+++ b/blog/breaking-down-data-silos-with-an-apache-doris-based-cdp.md
@@ -130,4 +130,4 @@ In Apache Doris, this is implemented by the BITMAP
functions: `BITMAP_CONTAINS`
## Conclusion
-From CDP 1.0 to CDP 2.0, the insurance company adopts Apache Doris, a unified
data warehouse, to replace Spark+Impala+HBase+NebulaGraph. That increases their
data processing efficiency by breaking down the data silos and streamlining
data processing pipelines. In CDP 3.0 to come, they want to group their
customer by combining real-time tags and offline tags for more diversified and
flexible analysis. The [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite [...]
\ No newline at end of file
+From CDP 1.0 to CDP 2.0, the insurance company adopts Apache Doris, a unified
data warehouse, to replace Spark+Impala+HBase+NebulaGraph. That increases their
data processing efficiency by breaking down the data silos and streamlining
data processing pipelines. In CDP 3.0 to come, they want to group their
customer by combining real-time tags and offline tags for more diversified and
flexible analysis. The [Apache Doris community](https://doris.apache.org/slack)
and the [VeloDB](https://ww [...]
\ No newline at end of file
diff --git a/blog/cross-cluster-replication-for-read-write.md
b/blog/cross-cluster-replication-for-read-write.md
index d451dc7b2bd..cfac43ed6d5 100644
--- a/blog/cross-cluster-replication-for-read-write.md
+++ b/blog/cross-cluster-replication-for-read-write.md
@@ -112,6 +112,6 @@ In the grocery store brand's case, they need to synchronize
a few tables from th
Using CCR in Apache Doris, the grocery store brand separates reading and
writing workloads into different clusters and thus improves overall system
stability. This solution delivers a real-time data synchronization latency of
about 1 second. To further ensure normal functioning, it has a real-time
monitoring and alerting mechanism so any issue will be notified and attended to
instantly, and a contingency plan to guarantee uninterrupted query services. It
also supports partition-based dat [...]
-CCR is also applicable when you need to build multiple data centers or derive
a test dataset from your production environment. For further guidance on CCR,
join the [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+CCR is also applicable when you need to build multiple data centers or derive
a test dataset from your production environment. For further guidance on CCR,
join the [Apache Doris community](https://doris.apache.org/slack).
\ No newline at end of file
diff --git
a/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
b/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
index ad45220081f..3afda6b56ee 100644
---
a/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
+++
b/blog/data-analysis-for-live-streaming-what-happens-in-real-time-is-analyzed-in-real-time.md
@@ -214,7 +214,7 @@ limit 1,10;
## Conclusion
-Data analysis in live streaming is challenging for the underlying database,
but it is also where the key competitiveness of Apache Doris comes to play.
First of all, Apache Doris can handle most data processing workloads, so
platform builders don't have to worry about putting many components together
and consequential maintenance issues. Secondly, it has a lot of
query-accelerating features, including but not limited to indexes. After
tackling the speed issues, the [Apache Doris develope [...]
+Data analysis in live streaming is challenging for the underlying database,
but it is also where the key competitiveness of Apache Doris comes to play.
First of all, Apache Doris can handle most data processing workloads, so
platform builders don't have to worry about putting many components together
and consequential maintenance issues. Secondly, it has a lot of
query-accelerating features, including but not limited to indexes. After
tackling the speed issues, the [Apache Doris develope [...]
diff --git
a/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
b/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
index f4500f7dbb6..ccbc5cddc80 100644
---
a/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
+++
b/blog/empowering-cyber-security-by-enabling-seven-times-faster-log-analysis.md
@@ -140,4 +140,4 @@ Apart from cluster management, Doris Manager provides a
visualized WebUI for log
-After a month-long trial run, they officially replaced their old LSAS with the
Apache Doris-based system for production, and achieved great results as they
expected. Now, they ingest their 100s of billions of new logs every day via the
[Routine
Load](https://doris.apache.org/docs/dev/data-operate/import/import-way/routine-load-manual/)
method at a speed 3 times as fast as before. Among the 7-time overall query
performance increase, they benefit from a speedup of over 20 times in full-tex
[...]
+After a month-long trial run, they officially replaced their old LSAS with the
Apache Doris-based system for production, and achieved great results as they
expected. Now, they ingest their 100s of billions of new logs every day via the
[Routine
Load](https://doris.apache.org/docs/dev/data-operate/import/import-way/routine-load-manual/)
method at a speed 3 times as fast as before. Among the 7-time overall query
performance increase, they benefit from a speedup of over 20 times in full-tex
[...]
diff --git a/blog/evolution-of-the-apache-doris-execution-engine.md
b/blog/evolution-of-the-apache-doris-execution-engine.md
index 48ee6b571f4..5991325f4f0 100644
--- a/blog/evolution-of-the-apache-doris-execution-engine.md
+++ b/blog/evolution-of-the-apache-doris-execution-engine.md
@@ -230,4 +230,4 @@ From the Volcano Model to the Pipeline Execution Engine,
Apache Doris 2.0.0 has
What's next in our roadmap is to support spilling data to disk in PipelineX to
further improve query speed and system reliability. We also plan to advance
further in terms of automation, such as self-adaptive concurrency and auto
execution plan optimization, accompanied by NUMA technologies to harvest better
performance from hardware resources.
-If you want to talk to the amazing Doris developers who lead these changes,
you are more than welcome to join the [Apache
Doris](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
community.
\ No newline at end of file
+If you want to talk to the amazing Doris developers who lead these changes,
you are more than welcome to join the [Apache
Doris](https://doris.apache.org/slack) community.
\ No newline at end of file
diff --git
a/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
b/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
index 81d9cd7f269..7c739fbaf16 100644
---
a/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
+++
b/blog/from-elasticsearch-to-apache-doris-upgrading-an-observability-platform.md
@@ -161,8 +161,8 @@ Currently, the Variant type requires extra type assertion,
we plan to automate t
## Conclusion
-GuanceDB's transition from Elasticsearch to Apache Doris showcases a big
stride in improving data processing speed and reducing costs. For these
purposes, Apache Doris has optimized itself in the two major aspects of data
processing: data integration and data analysis. It has expanded its schemaless
support to flexibly accommodate more data types, introduced features like
inverted index and tiered storage to enable faster and more cost-effective
queries. Evolution is an ongoing process. [...]
+GuanceDB's transition from Elasticsearch to Apache Doris showcases a big
stride in improving data processing speed and reducing costs. For these
purposes, Apache Doris has optimized itself in the two major aspects of data
processing: data integration and data analysis. It has expanded its schemaless
support to flexibly accommodate more data types, introduced features like
inverted index and tiered storage to enable faster and more cost-effective
queries. Evolution is an ongoing process. [...]
Check Apache Doris GitHub [repo](https://github.com/apache/doris)
-Find Apache Doris makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
+Find Apache Doris makers on [Slack](https://doris.apache.org/slack)
diff --git
a/blog/from-presto-trino-clickhouse-and-hive-to-apache-doris-sql-convertor-for-easy-migration.md
b/blog/from-presto-trino-clickhouse-and-hive-to-apache-doris-sql-convertor-for-easy-migration.md
index c8adf0bb55b..577dec6fcd0 100644
---
a/blog/from-presto-trino-clickhouse-and-hive-to-apache-doris-sql-convertor-for-easy-migration.md
+++
b/blog/from-presto-trino-clickhouse-and-hive-to-apache-doris-sql-convertor-for-easy-migration.md
@@ -174,7 +174,7 @@ After deployment, you can access the service by `ip:8080`
via your local browser
2. The Doris SQL Convertor supports 239 UNION ALL conversions at most.
:::
-Join the [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
to seek guidance from the Doris makers or provide your feedback!
+Join the [Apache Doris community](https://doris.apache.org/slack) to seek
guidance from the Doris makers or provide your feedback!
diff --git
a/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
b/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
index ad6893e5da8..068d6095cfe 100644
---
a/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
+++
b/blog/how-big-data-is-saving-lives-in-real-time-iov-data-analytics-helps-prevent-accidents.md
@@ -110,5 +110,5 @@ Building a data platform to suit your use case is not easy,
I hope this post hel
Apache Doris [GitHub repo](https://github.com/apache/doris)
-Find Apache Doris makers on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
+Find Apache Doris makers on [Slack](https://doris.apache.org/slack)
diff --git
a/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
b/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
index 6e7094e4c60..a4526f2bef5 100644
---
a/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
+++
b/blog/introduction-to-apache-doris-a-next-generation-real-time-data-warehouse.md
@@ -171,4 +171,4 @@ Roughly speaking, for a data asset consisting of 80% cold
data, tiered storage w
## The Apache Doris Community
-This is an overview of Apache Doris, an open-source real-time data warehouse.
It is actively evolving with an agile release schedule, and the
[community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
embraces any questions, ideas, and feedback.
+This is an overview of Apache Doris, an open-source real-time data warehouse.
It is actively evolving with an agile release schedule, and the
[community](https://doris.apache.org/slack) embraces any questions, ideas, and
feedback.
diff --git
a/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
b/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
index 29031cc78da..626c6147a2d 100644
--- a/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
+++ b/blog/inverted-index-accelerates-text-searches-by-40-time-apache-doris.md
@@ -508,4 +508,4 @@ Inverted index has been available in Apache Doris for
almost a year and stood th
- **Self-defined tokenization**: provides a user-defined tokenizer to fit in
different use cases.
- **More data types**: Users will be able to create inverted index for complex
data types including Array and Map.
-If you encounter any issues while trying it out in Apache Doris or would like
to know more details, join our
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw)
community and talk to us!
+If you encounter any issues while trying it out in Apache Doris or would like
to know more details, join our [Slack](https://doris.apache.org/slack)
community and talk to us!
diff --git a/blog/job-scheduler-for-task-automation.md
b/blog/job-scheduler-for-task-automation.md
index b4575520ba9..c21b4e98a6b 100644
--- a/blog/job-scheduler-for-task-automation.md
+++ b/blog/job-scheduler-for-task-automation.md
@@ -202,7 +202,7 @@ In addition, for transactional tasks, the Job Scheduler can
ensure data consiste
The Doris Job Scheduler is a Swiss Army Knife. It is not only useful in ETL
and data lake analytics as we mentioned, but also critical for the
implementation of [asynchronous materialized
views](https://doris.apache.org/docs/query/view-materialized-view/async-materialized-view).
An asynchronous materialized view is a pre-computed result set. Unlike normal
materialized views, it can be built on multiple tables. Thus, as you can
imagine, changes in any of the source tables will lead to the [...]
-Where are we going with the Doris Job Scheduler? The [Apache Doris developer
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
is looking at:
+Where are we going with the Doris Job Scheduler? The [Apache Doris developer
community](https://doris.apache.org/slack) is looking at:
- Displaying the distribution of tasks executed in different time slots on the
WebUI.
diff --git a/blog/log-analysis-elasticsearch-vs-apache-doris.md
b/blog/log-analysis-elasticsearch-vs-apache-doris.md
index 61b4df50de8..a23660b5f9c 100644
--- a/blog/log-analysis-elasticsearch-vs-apache-doris.md
+++ b/blog/log-analysis-elasticsearch-vs-apache-doris.md
@@ -351,4 +351,4 @@ SELECT * FROM log_table WHERE request MATCH_ALL 'image faq'
ORDER BY ts DESC LIM
If you are looking for an efficient log analytic solution, Apache Doris is
friendly to anyone equipped with SQL knowledge; if you find friction with the
ELK stack, try Apache Doris provides better schema-free support, enables faster
data writing and queries, and brings much less storage burden.
-But we won't stop here. We are going to provide more features to facilitate
log analysis. We plan to add more complicated data types to inverted index, and
support BKD index to make Apache Doris a fit for geo data analysis. We also
plan to expand capabilities in semi-structured data analysis, such as working
on the complex data types (Array, Map, Struct, JSON) and high-performance
string matching algorithm. And we welcome any [user feedback and development
advice](https://join.slack.com/ [...]
+But we won't stop here. We are going to provide more features to facilitate
log analysis. We plan to add more complicated data types to inverted index, and
support BKD index to make Apache Doris a fit for geo data analysis. We also
plan to expand capabilities in semi-structured data analysis, such as working
on the complex data types (Array, Map, Struct, JSON) and high-performance
string matching algorithm. And we welcome any [user feedback and development
advice](https://doris.apache.or [...]
diff --git a/blog/migrate-lakehouse-from-bigquery-to-doris.md
b/blog/migrate-lakehouse-from-bigquery-to-doris.md
index ce3207d72f9..e66ca62735b 100644
--- a/blog/migrate-lakehouse-from-bigquery-to-doris.md
+++ b/blog/migrate-lakehouse-from-bigquery-to-doris.md
@@ -32,7 +32,7 @@ under the License.
-->
:::tip Special Thanks
-The Apache Doris community would like to extend our gratitude to Dien for
sharing his valuable experience and best practices in migrating from BigQuery
to Apache Doris in this insightful and informative article. Dien is also an
active member of the Apache Doris open-source
[community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ),
and we are truly appreciative of his ongoing support.
+The Apache Doris community would like to extend our gratitude to Dien for
sharing his valuable experience and best practices in migrating from BigQuery
to Apache Doris in this insightful and informative article. Dien is also an
active member of the Apache Doris open-source
[community](https://doris.apache.org/slack), and we are truly appreciative of
his ongoing support.
:::
This article is written by [Dien, Tran
Thanh](https://www.linkedin.com/in/dien-tran-thanh-19275b14a/) and originally
posted on
[Medium](https://dientt.medium.com/migrate-data-platform-từ-bigquery-sang-apache-doris-giúp-giảm-chi-phí-từ-6-000-xuống-còn-1-500-40ba9b22967e).
@@ -183,7 +183,7 @@ The implementation was carried out by 1 Data Engineer, 1
Software Engineer, and
- Data replication between nodes can sometimes lose synchronization due to
network issues or other reasons, and the automatic replication retry mechanism
may not be successful. In such cases, it is necessary to set up an external
worker mechanism for automatic handling (Doris manages a storage unit called
Tablet. The metadata on each node records the ETL data into a specific table,
and the metadata version gets updated. Doris provides a SQL-based method to
handle desynchronization).
-- New versions may occasionally have bugs, so it's recommended to check if the
[community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
has reported any issues before deciding to upgrade.
+- New versions may occasionally have bugs, so it's recommended to check if the
[community](https://doris.apache.org/slack) has reported any issues before
deciding to upgrade.
- Limited support for processing Vietnamese text, with the full-text search
feature not performing well in Vietnamese.
diff --git a/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
b/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
index ff234ecbcaa..85dd1b1218a 100644
--- a/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
+++ b/blog/migrating-from-clickhouse-to-apache-doris-what-happened.md
@@ -160,4 +160,4 @@ In terms of CPU and memory consumption, Apache Doris
maintained stable cluster l
## Future Directions
-As the migration goes on, the user works closely with the [Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw),
and their feedback has contributed to the making of [Apache Doris
2.0.0](https://doris.apache.org/docs/dev/releasenotes/release-2.0.0/). We will
continue assisting them in their migration from Kylin and Druid to Doris, and
we look forward to see their Doris-based unified data platform come into being.
+As the migration goes on, the user works closely with the [Doris
community](https://doris.apache.org/slack), and their feedback has contributed
to the making of [Apache Doris
2.0.0](https://doris.apache.org/docs/dev/releasenotes/release-2.0.0/). We will
continue assisting them in their migration from Kylin and Druid to Doris, and
we look forward to see their Doris-based unified data platform come into being.
diff --git a/blog/multi-tenant-workload-isolation-in-apache-doris.md
b/blog/multi-tenant-workload-isolation-in-apache-doris.md
index f65ed34c8e9..3193b30cca4 100644
--- a/blog/multi-tenant-workload-isolation-in-apache-doris.md
+++ b/blog/multi-tenant-workload-isolation-in-apache-doris.md
@@ -222,4 +222,4 @@ In future releases, we will keep improving user experience
of the Workload Group
- The main idea of Resource Tag is to group the BE nodes, while that of
Workload Group is to further divide the resources of a single BE node. For
users to grasp these ideas, they need to learn about the concept of BE nodes in
Doris first. However, from an operational perspective, users only need to
understand the resource consumption percentage of each of their workloads and
what priority they should have when cluster load is saturated. Thus, we will
try and figure out a way to flatten [...]
-For further assistance on workload isolation in Apache Doris, join the [Apache
Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
\ No newline at end of file
+For further assistance on workload isolation in Apache Doris, join the [Apache
Doris community](https://doris.apache.org/slack).
\ No newline at end of file
diff --git a/blog/release-note-2.0.0.md b/blog/release-note-2.0.0.md
index a5380d4bf50..28f7316306c 100644
--- a/blog/release-note-2.0.0.md
+++ b/blog/release-note-2.0.0.md
@@ -235,5 +235,5 @@ This feature allows for higher availability of data,
read/write workload separat
To make Apache Doris 2.0.0 production-ready, we invited hundreds of enterprise
users to engage in the testing and optimized it for better performance,
stability, and usability. In the next phase, we will continue responding to
user needs with agile release planning. We plan to launch 2.0.1 in late August
and 2.0.2 in September, as we keep fixing bugs and adding new features. We also
plan to release an early version of 2.1 in September to bring a few
long-requested capabilities to you. Fo [...]
-If you have any questions or ideas when investigating, testing, and deploying
Apache Doris, please find us on
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
Our developers will be happy to hear them and provide targeted support.
+If you have any questions or ideas when investigating, testing, and deploying
Apache Doris, please find us on [Slack](https://doris.apache.org/slack). Our
developers will be happy to hear them and provide targeted support.
diff --git a/blog/release-note-2.1.0.md b/blog/release-note-2.1.0.md
index 684f3235538..dd33ab958f7 100644
--- a/blog/release-note-2.1.0.md
+++ b/blog/release-note-2.1.0.md
@@ -40,7 +40,7 @@ Dear Apache Doris community, we are thrilled to announce the
advent of Apache Do
- **Better workload management**: optimizations of the Workload Group
mechanism for higher performance stability and the display of SQL resource
consumption in the runtime.
-We appreciate the 237 contributors who made nearly 6000 commits in total to
the Apache Doris project, and the nearly 100 enterprise users who provided
valuable feedback. We will keep aiming for the stars with our agile release
planning, and we appreciate your feedback in the [Apache Doris developer and
user
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
+We appreciate the 237 contributors who made nearly 6000 commits in total to
the Apache Doris project, and the nearly 100 enterprise users who provided
valuable feedback. We will keep aiming for the stars with our agile release
planning, and we appreciate your feedback in the [Apache Doris developer and
user community](https://doris.apache.org/slack).
**Download from GitHub**: https://github.com/apache/doris/releases
diff --git a/blog/release-note-3.0.0.md b/blog/release-note-3.0.0.md
index 03de9a1565b..1a238f88e16 100644
--- a/blog/release-note-3.0.0.md
+++ b/blog/release-note-3.0.0.md
@@ -463,7 +463,7 @@ Before the official release of version 3.0, the
compute-storage decoupled mode o
We highly recommend users with compute-storage decoupling needs to download
version 3.0 and experience it firsthand.
-Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
and engage directly with the core developers.
+Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris community](https://doris.apache.org/slack) and engage directly
with the core developers.
## Credits
diff --git a/blog/tencent-music-migrate-elasticsearch-to-doris.md
b/blog/tencent-music-migrate-elasticsearch-to-doris.md
index 4a09a72aa2e..848eb3bf536 100644
--- a/blog/tencent-music-migrate-elasticsearch-to-doris.md
+++ b/blog/tencent-music-migrate-elasticsearch-to-doris.md
@@ -186,4 +186,4 @@ The migration from Elasticsearch to Apache Doris has
yielded impressive gains. W
By replacing its Elasticsearch cluster with Doris, TME has unified its content
library's search and analytics engines into a single, streamlined platform. The
system now supports complex custom tag-based segmentation with sub-second
response. The next-phase plan of TME is to explore broader use cases of Apache
Doris and prepare to adopt the [compute-storage decoupled
mode](https://doris.apache.org/docs/3.0/compute-storage-decoupled/overview) to
drive even greater cost efficiency.
-For direct communication, real-world insights, and best practices, join
[#elasticsearch-to-doris](https://apachedoriscommunity.slack.com/archives/C08CQKX20R5)
channel in the [Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ).
\ No newline at end of file
+For direct communication, real-world insights, and best practices, join
[#elasticsearch-to-doris](https://apachedoriscommunity.slack.com/archives/C08CQKX20R5)
channel in the [Apache Doris community](https://doris.apache.org/slack).
\ No newline at end of file
diff --git a/blog/variant-in-apache-doris-2.1.md
b/blog/variant-in-apache-doris-2.1.md
index 55b1f5bd501..ee1c394f1c6 100644
--- a/blog/variant-in-apache-doris-2.1.md
+++ b/blog/variant-in-apache-doris-2.1.md
@@ -428,4 +428,4 @@ The Doris-based solution also delivers lower CPU usage in
data writing and highe
The Variant data type has stood the test of many users before the official
release of Apache Doris 2.1.0. It is production-available now. In the future,
we plan to realize more lightweight changes for Variant to facilitate data
modeling.
-For more information about Variant and guides on how to build a
semi-structured data analytics solution for your case, come talk to the [Apache
Doris developer
team](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2unfw3a3q-MtjGX4pAd8bCGC1UV0sKcw).
\ No newline at end of file
+For more information about Variant and guides on how to build a
semi-structured data analytics solution for your case, come talk to the [Apache
Doris developer team](https://doris.apache.org/slack).
\ No newline at end of file
diff --git
a/blog/why-apache-doris-is-best-alternatives-for-real-time-analytics.md
b/blog/why-apache-doris-is-best-alternatives-for-real-time-analytics.md
index 8d414e4b727..57b6e4c9700 100644
--- a/blog/why-apache-doris-is-best-alternatives-for-real-time-analytics.md
+++ b/blog/why-apache-doris-is-best-alternatives-for-real-time-analytics.md
@@ -397,7 +397,7 @@ By 2023, the value of Doris with inverted indexes became
increasingly evident, l
The growth momentum has continued, and as of 2024, we are experiencing rapid
expansion, with over 100 companies now leveraging Doris to replace
Elasticsearch.
-Looking ahead, I am very much looking forward to what 2025 will bring. This
progress, advancing from the ground up to such significant milestones, has been
made possible by the incredible support from the Doris community users and
developers. We encourage everyone to join the [Apache Doris Slack
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2zlwvmzon-NIb2rz50rIhcflGAFpYjDQ)
and join the dedicated channel
[#elasticsearch-to-doris](https://apachedoriscommunity.s [...]
+Looking ahead, I am very much looking forward to what 2025 will bring. This
progress, advancing from the ground up to such significant milestones, has been
made possible by the incredible support from the Doris community users and
developers. We encourage everyone to join the [Apache Doris Slack
community](https://doris.apache.org/slack) and join the dedicated channel
[#elasticsearch-to-doris](https://apachedoriscommunity.slack.com/archives/C08CQKX20R5),
where you can receive technical a [...]
More on Apache Doris:
diff --git a/community/how-to-contribute/contribute-to-doris.md
b/community/how-to-contribute/contribute-to-doris.md
index c41e799553c..5c851909c1e 100644
--- a/community/how-to-contribute/contribute-to-doris.md
+++ b/community/how-to-contribute/contribute-to-doris.md
@@ -44,7 +44,7 @@ For the first time in Doris community, you can:
* Join Doris Wechat Group (add WeChat-ID: morningman-cmy, note: join Doris
Group) and ask questions at any time.
-* Enter Doris's
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-35mzao67o-BrpU70FNKPyB6UlgpXf8_w)
+* Enter Doris's [Slack](https://doris.apache.org/slack)
Learn the development trends of Doris project in time and give your opinions
on the topics you are concerned about.
diff --git a/community/join-community.md b/community/join-community.md
index 30ec4925141..ced9f6c27d8 100644
--- a/community/join-community.md
+++ b/community/join-community.md
@@ -39,7 +39,7 @@ We have graduated from Apache incubator successfully and
become an Top-Level Pro
Learn our latest techniques, get inspirations from our rich use cases, and see
what the community has been up to !
-- Join our heated discussions - 💬
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-35mzao67o-BrpU70FNKPyB6UlgpXf8_w)
📇 [Github](https://github.com/apache/doris)
+- Join our heated discussions - 💬 [Slack](https://doris.apache.org/slack) 📇
[Github](https://github.com/apache/doris)
- Use cases and tech insight - 📭 [Twitter](https://twitter.com/doris_apache)
diff --git a/docs/releasenotes/v3.0/release-3.0.0.md
b/docs/releasenotes/v3.0/release-3.0.0.md
index e0694e7b55e..36a20fe1dc2 100644
--- a/docs/releasenotes/v3.0/release-3.0.0.md
+++ b/docs/releasenotes/v3.0/release-3.0.0.md
@@ -441,7 +441,7 @@ Before the official release of version 3.0, the
compute-storage decoupled mode o
We highly recommend users with compute-storage decoupling needs to download
version 3.0 and experience it firsthand.
-Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
and engage directly with the core developers.
+Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris community](https://doris.apache.org/slack) and engage directly
with the core developers.
## Credits
diff --git a/docusaurus.config.js b/docusaurus.config.js
index 17b8d9179d1..337d434e1c1 100644
--- a/docusaurus.config.js
+++ b/docusaurus.config.js
@@ -142,6 +142,10 @@ const config = {
{
from: '/docs/4.0/releasenotes/v4.0/release-4.0.0/',
to: '/docs/4.x/releasenotes/v4.0/release-4.0.0'
+ },
+ {
+ from: '/slack',
+ to:
'https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-3b8tlr3le-Z~IrrVxkzqniFjhL17d1oQ'
}
],
createRedirects(existingPath) {
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/how-to-contribute/contribute-to-doris.md
b/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/how-to-contribute/contribute-to-doris.md
index abd294b203b..51cd94642f1 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/how-to-contribute/contribute-to-doris.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/how-to-contribute/contribute-to-doris.md
@@ -43,7 +43,7 @@ under the License.
* 加入 Doris 微信群 (加微信号：morningman-cmy, 备注：加入 Doris 群) 随时提问；
-* 加入
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-35mzao67o-BrpU70FNKPyB6UlgpXf8_w);
+* 加入 [Slack](https://doris.apache.org/slack);
通过以上方式及时了解 Doris 项目的开发动态并为您关注的话题发表意见。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/join-community.md
b/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/join-community.md
index 04c9b7621f3..c641082e97b 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/join-community.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs-community/current/join-community.md
@@ -38,7 +38,7 @@ under the License.
一起加入 Apache Doris 社区，了解头部企业如何基于 Apache Doris 构建统一实时数仓，从技术见解获得更多灵感！
-- 加入社群参与讨论 - 💬
[Slack](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-35mzao67o-BrpU70FNKPyB6UlgpXf8_w)
📇 [Github](https://github.com/apache/doris)
+- 加入社群参与讨论 - 💬 [Slack](https://doris.apache.org/slack) 📇
[Github](https://github.com/apache/doris)
- 用户案例与技术见解 - 📭 [Twitter](https://twitter.com/doris_apache)
diff --git a/src/pages/index.tsx b/src/pages/index.tsx
index e937c18e420..f019462ba0d 100644
--- a/src/pages/index.tsx
+++ b/src/pages/index.tsx
@@ -35,7 +35,7 @@ export default function Home(): JSX.Element {
},
{
label: <Translate id="homepage.banner.button2">Join
Slack</Translate>,
- link:
'https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-3b8tlr3le-Z~IrrVxkzqniFjhL17d1oQ',
+ link: 'https://doris.apache.org/slack',
type: 'ghost',
},
];
@@ -284,7 +284,7 @@ export default function Home(): JSX.Element {
</defs>
</svg>
),
- href:
'https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-3b8tlr3le-Z~IrrVxkzqniFjhL17d1oQ',
+ href: 'https://doris.apache.org/slack',
},
{
title: <Translate id="community.title.c4">Twitter</Translate>,
diff --git a/src/theme/Footer/index.tsx b/src/theme/Footer/index.tsx
index 213a4a78e48..009a441feaf 100644
--- a/src/theme/Footer/index.tsx
+++ b/src/theme/Footer/index.tsx
@@ -89,7 +89,7 @@ function Footer(): React.ReactElement | null {
<TwitterIcon />
</a>
<a
-
href="https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-3b8tlr3le-Z~IrrVxkzqniFjhL17d1oQ";
+ href="https://doris.apache.org/slack";
title="slack"
target="_blank"
className="item"
diff --git a/src/theme/Navbar/Content/components/NavbarCommon.tsx
b/src/theme/Navbar/Content/components/NavbarCommon.tsx
index 2b41537cebd..b4ca73a86e1 100644
--- a/src/theme/Navbar/Content/components/NavbarCommon.tsx
+++ b/src/theme/Navbar/Content/components/NavbarCommon.tsx
@@ -58,7 +58,7 @@ export const NavbarCommonRight = ({ star }:
NavbarCommonRightProps) => {
{star && <div className="gh-count
text-[1rem]/[1rem]">{star}k</div>}
<Link
className="slack-btn desktop header-right-button-slack"
-
href="https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-3b8tlr3le-Z~IrrVxkzqniFjhL17d1oQ";
+ href="https://doris.apache.org/slack";
target="_blank"
></Link>
</>
diff --git a/src/theme/TOC/index.tsx b/src/theme/TOC/index.tsx
index ddf4b298ea9..8f3c53ec3ab 100644
--- a/src/theme/TOC/index.tsx
+++ b/src/theme/TOC/index.tsx
@@ -121,7 +121,7 @@ export default function TOC({ className, ...props }:
Props): React.ReactElement
<Link
className="toc-icon-content group"
to={
-
'https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-3b8tlr3le-Z~IrrVxkzqniFjhL17d1oQ'
+ 'https://doris.apache.org/slack'
}
>
<div style={{ padding: '2px' }}>
diff --git a/versioned_docs/version-2.1/releasenotes/v3.0/release-3.0.0.md
b/versioned_docs/version-2.1/releasenotes/v3.0/release-3.0.0.md
index f938ada2817..e2f06029307 100644
--- a/versioned_docs/version-2.1/releasenotes/v3.0/release-3.0.0.md
+++ b/versioned_docs/version-2.1/releasenotes/v3.0/release-3.0.0.md
@@ -441,7 +441,7 @@ Before the official release of version 3.0, the
compute-storage decoupled mode o
We highly recommend users with compute-storage decoupling needs to download
version 3.0 and experience it firsthand.
-Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
and engage directly with the core developers.
+Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris community](https://doris.apache.org/slack) and engage directly
with the core developers.
## Credits
diff --git a/versioned_docs/version-3.x/releasenotes/v3.0/release-3.0.0.md
b/versioned_docs/version-3.x/releasenotes/v3.0/release-3.0.0.md
index 19cb88b848b..cc0775b1c00 100644
--- a/versioned_docs/version-3.x/releasenotes/v3.0/release-3.0.0.md
+++ b/versioned_docs/version-3.x/releasenotes/v3.0/release-3.0.0.md
@@ -441,7 +441,7 @@ Before the official release of version 3.0, the
compute-storage decoupled mode o
We highly recommend users with compute-storage decoupling needs to download
version 3.0 and experience it firsthand.
-Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
and engage directly with the core developers.
+Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris community](https://doris.apache.org/slack) and engage directly
with the core developers.
## Credits
diff --git a/versioned_docs/version-4.x/releasenotes/v3.0/release-3.0.0.md
b/versioned_docs/version-4.x/releasenotes/v3.0/release-3.0.0.md
index e0694e7b55e..36a20fe1dc2 100644
--- a/versioned_docs/version-4.x/releasenotes/v3.0/release-3.0.0.md
+++ b/versioned_docs/version-4.x/releasenotes/v3.0/release-3.0.0.md
@@ -441,7 +441,7 @@ Before the official release of version 3.0, the
compute-storage decoupled mode o
We highly recommend users with compute-storage decoupling needs to download
version 3.0 and experience it firsthand.
-Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris
community](https://join.slack.com/t/apachedoriscommunity/shared_invite/zt-2gmq5o30h-455W226d79zP3L96ZhXIoQ)
and engage directly with the core developers.
+Going forward, we will accelerate our release iteration cycle to deliver a
more stable version experience for all users. Feel free to join us in the
[Apache Doris community](https://doris.apache.org/slack) and engage directly
with the core developers.
## Credits
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
