This is an automated email from the ASF dual-hosted git repository.
yiguolei 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 6beff8f6078 [Update] Change default version and some other fix (#3134)
6beff8f6078 is described below
commit 6beff8f60780e5080d098a53015bbac1d035dd8d
Author: zhuwei <[email protected]>
AuthorDate: Fri Dec 5 10:41:35 2025 +0800
[Update] Change default version and some other fix (#3134)
## Versions
- [ ] dev
- [ ] 4.x
- [ ] 3.x
- [ ] 2.1
## Languages
- [ ] Chinese
- [ ] English
## Docs Checklist
- [ ] Checked by AI
- [ ] Test Cases Built
---------
Co-authored-by: zhuwei <[email protected]>
---
docs/observability/log.md | 2 +-
docs/releasenotes/all-release.md | 4 +++-
.../sql-functions/scalar-functions/string-functions/week-ceil.md | 6 ------
.../sql-functions/scalar-functions/string-functions/week-floor.md | 6 ------
.../current/releasenotes/all-release.md | 4 +++-
.../version-3.x/releasenotes/all-release.md | 4 +++-
.../version-4.x/releasenotes/all-release.md | 4 +++-
src/constant/version.ts | 2 +-
versioned_docs/version-2.1/observability/log.md | 2 +-
versioned_docs/version-3.x/benchmark/tpcds.md | 2 +-
versioned_docs/version-3.x/observability/log.md | 2 +-
versioned_docs/version-3.x/releasenotes/all-release.md | 4 +++-
versioned_docs/version-4.x/observability/log.md | 2 +-
versioned_docs/version-4.x/releasenotes/all-release.md | 4 +++-
14 files changed, 24 insertions(+), 24 deletions(-)
diff --git a/docs/observability/log.md b/docs/observability/log.md
index 9455a298c49..6eac7b1d540 100644
--- a/docs/observability/log.md
+++ b/docs/observability/log.md
@@ -33,7 +33,7 @@ Before deploying the cluster, you need to estimate the
hardware resources requir
For example, suppose that the daily data increment is 100 TB, the data
compression ratio is 5, the number of data copies is 2, the storage duration of
hot data is 3 days, the storage duration of cold data is 30 days, the ratio of
the peak write throughput to the average write throughput is 200%, the write
throughput of a single-core CUP is 10 MB/s, and 50% of CPU resources are
reserved for data querying, one can estimate that:
-**compute-storage-integerated mode**
+**compute-storage-integrated mode**
- 3 FE servers are required, each configured with a 16-core CPU, 64 GB memory,
and an 1 100 GB SSD disk.
- 30 BE servers are required, each configured with a 32-core CPU, 256 GB
memory, and 8 625 GB SSD disks.
- S3 object storage space 540 TB
diff --git a/docs/releasenotes/all-release.md b/docs/releasenotes/all-release.md
index a2d15b65ad8..5ea5d78f2d3 100644
--- a/docs/releasenotes/all-release.md
+++ b/docs/releasenotes/all-release.md
@@ -12,7 +12,7 @@ This document presents a summary of Apache Doris versions
released within one ye
<br />
-🎉 Version 3.1.2 is released. Check out the 🔗[Release
Notes](../releasenotes/v3.1/release-3.1.2) here. Doris 3.1 introduces a sparse
column and schema template for the VARIANT data type, making it more efficient
to store and query large datasets with dynamic fields, such as logs and JSON
data. For lakehouse capabilities, it enhances asynchronous materialized views
and expands support for Iceberg and Paimon to build a stronger bridge between
data lakes and data warehouses.
+🎉 Version 3.1.3 is released. Check out the 🔗[Release
Notes](../releasenotes/v3.1/release-3.1.3) here. Doris 3.1 introduces a sparse
column and schema template for the VARIANT data type, making it more efficient
to store and query large datasets with dynamic fields, such as logs and JSON
data. For lakehouse capabilities, it enhances asynchronous materialized views
and expands support for Iceberg and Paimon to build a stronger bridge between
data lakes and data warehouses.
<br />
@@ -27,6 +27,8 @@ This document presents a summary of Apache Doris versions
released within one ye
<br />
+- [2025-11-24, Apache Doris 3.1.3 is
released](../releasenotes/v3.1/release-3.1.3.md)
+
- [2025-11-08, Apache Doris 4.0.1 is
released](../releasenotes/v4.0/release-4.0.1.md)
- [2025-10-27, Apache Doris 3.1.2 is
released](../releasenotes/v3.1/release-3.1.2.md)
diff --git
a/docs/sql-manual/sql-functions/scalar-functions/string-functions/week-ceil.md
b/docs/sql-manual/sql-functions/scalar-functions/string-functions/week-ceil.md
deleted file mode 100644
index d56571ab223..00000000000
---
a/docs/sql-manual/sql-functions/scalar-functions/string-functions/week-ceil.md
+++ /dev/null
@@ -1,6 +0,0 @@
----
-{
- "title": "WEEK_CEIL",
- "language": "zh-CN"
-}
----
diff --git
a/docs/sql-manual/sql-functions/scalar-functions/string-functions/week-floor.md
b/docs/sql-manual/sql-functions/scalar-functions/string-functions/week-floor.md
deleted file mode 100644
index abc059c1395..00000000000
---
a/docs/sql-manual/sql-functions/scalar-functions/string-functions/week-floor.md
+++ /dev/null
@@ -1,6 +0,0 @@
----
-{
- "title": "WEEK_FLOOR",
- "language": "zh-CN"
-}
----
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/all-release.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/all-release.md
index 7d5ff6ed5a2..358f04fd390 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/all-release.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/all-release.md
@@ -13,7 +13,7 @@
🎉 4.0.1 版本已于 2025 年 11 月 08
日正式发布，详情可查看[版本发布](../releasenotes/v4.0/release-4.0.1)。新版本通过 AI
与搜索能力的深度融合、离线计算的稳定性提升、性能与易用性的双重优化，进一步拓宽了数据库的应用边界，可更好地支撑企业从传统 BI 分析到 AI
智能检索、从实时查询到大规模离线批处理的全场景数据分析需求。无论是互联网、金融、零售等行业的实时报表、用户行为分析，还是政务、医疗领域的文档检索、大规模数据批处理，新版本
Doris 都将为用户提供更高效、更可靠的数据分析体验。
<br />
-🎉 3.1.2 版本已于 2025 年 10 月 27
日正式发布，详情可查看[版本发布](../releasenotes/v3.1/release-3.1.2)。Apache Doris 3.1
是半结构化分析领域的里程碑，引入了稀疏列和模板化
schema，显著提升了查询和索引性能。它还显著增强了湖仓一体能力，通过异步物化视图和优化连接属性，实现了数据湖和数据仓的无缝集成。新版本在存储引擎上提供了灵活列更新，并通过分区裁剪和基于数据特征的优化器，实现了查询性能的巨大飞跃。
+🎉 3.1.3 版本已于 2025 年 11 月 24
日正式发布，详情可查看[版本发布](../releasenotes/v3.1/release-3.1.3)。Apache Doris 3.1
是半结构化分析领域的里程碑，引入了稀疏列和模板化
schema，显著提升了查询和索引性能。它还显著增强了湖仓一体能力，通过异步物化视图和优化连接属性，实现了数据湖和数据仓的无缝集成。新版本在存储引擎上提供了灵活列更新，并通过分区裁剪和基于数据特征的优化器，实现了查询性能的巨大飞跃。
<br />
🎉 3.0.8 版本已于 2025 年 09 月 19
日正式发布，详情可查看[版本发布](../releasenotes/v3.0/release-3.0.8)。从 3.0 版本开始，Apache Doris
除了支持计算存储一体模式外，还支持计算存储分离模式进行集群部署。借助将计算和存储层解耦的云原生架构，用户可以在多个计算集群之间实现查询负载的物理隔离，以及读写负载的隔离。
@@ -26,6 +26,8 @@
<br />
+- [2025-11-24, Apache Doris 3.1.3 版本发布](../releasenotes/v3.1/release-3.1.3.md)
+
- [2025-11-08, Apache Doris 4.0.1 版本发布](../releasenotes/v4.0/release-4.0.1.md)
- [2025-10-27, Apache Doris 3.1.2 版本发布](../releasenotes/v3.1/release-3.1.2.md)
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.x/releasenotes/all-release.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.x/releasenotes/all-release.md
index 766922e4341..27c3845dc1f 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.x/releasenotes/all-release.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.x/releasenotes/all-release.md
@@ -11,7 +11,7 @@
:::tip 最新发布
-🎉 3.1.2 版本已于 2025 年 10 月 27
日正式发布，详情可查看[版本发布](../releasenotes/v3.1/release-3.1.2)。Apache Doris 3.1
是半结构化分析领域的里程碑，引入了稀疏列和模板化
schema，显著提升了查询和索引性能。它还显著增强了湖仓一体能力，通过异步物化视图和优化连接属性，实现了数据湖和数据仓的无缝集成。新版本在存储引擎上提供了灵活列更新，并通过分区裁剪和基于数据特征的优化器，实现了查询性能的巨大飞跃。
+🎉 3.1.3 版本已于 2025 年 11 月 24
日正式发布，详情可查看[版本发布](../releasenotes/v3.1/release-3.1.3)。Apache Doris 3.1
是半结构化分析领域的里程碑，引入了稀疏列和模板化
schema，显著提升了查询和索引性能。它还显著增强了湖仓一体能力，通过异步物化视图和优化连接属性，实现了数据湖和数据仓的无缝集成。新版本在存储引擎上提供了灵活列更新，并通过分区裁剪和基于数据特征的优化器，实现了查询性能的巨大飞跃。
@@ -25,6 +25,8 @@
<br />
+- [2025-11-24, Apache Doris 3.1.3 版本发布](../releasenotes/v3.1/release-3.1.3.md)
+
- [2025-10-27, Apache Doris 3.1.2 版本发布](../releasenotes/v3.1/release-3.1.2.md)
- [2025-09-26, Apache Doris 3.1.1 版本发布](../releasenotes/v3.1/release-3.1.1.md)
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-4.x/releasenotes/all-release.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-4.x/releasenotes/all-release.md
index 7d5ff6ed5a2..358f04fd390 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-4.x/releasenotes/all-release.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-4.x/releasenotes/all-release.md
@@ -13,7 +13,7 @@
🎉 4.0.1 版本已于 2025 年 11 月 08
日正式发布，详情可查看[版本发布](../releasenotes/v4.0/release-4.0.1)。新版本通过 AI
与搜索能力的深度融合、离线计算的稳定性提升、性能与易用性的双重优化，进一步拓宽了数据库的应用边界，可更好地支撑企业从传统 BI 分析到 AI
智能检索、从实时查询到大规模离线批处理的全场景数据分析需求。无论是互联网、金融、零售等行业的实时报表、用户行为分析，还是政务、医疗领域的文档检索、大规模数据批处理，新版本
Doris 都将为用户提供更高效、更可靠的数据分析体验。
<br />
-🎉 3.1.2 版本已于 2025 年 10 月 27
日正式发布，详情可查看[版本发布](../releasenotes/v3.1/release-3.1.2)。Apache Doris 3.1
是半结构化分析领域的里程碑，引入了稀疏列和模板化
schema，显著提升了查询和索引性能。它还显著增强了湖仓一体能力，通过异步物化视图和优化连接属性，实现了数据湖和数据仓的无缝集成。新版本在存储引擎上提供了灵活列更新，并通过分区裁剪和基于数据特征的优化器，实现了查询性能的巨大飞跃。
+🎉 3.1.3 版本已于 2025 年 11 月 24
日正式发布，详情可查看[版本发布](../releasenotes/v3.1/release-3.1.3)。Apache Doris 3.1
是半结构化分析领域的里程碑，引入了稀疏列和模板化
schema，显著提升了查询和索引性能。它还显著增强了湖仓一体能力，通过异步物化视图和优化连接属性，实现了数据湖和数据仓的无缝集成。新版本在存储引擎上提供了灵活列更新，并通过分区裁剪和基于数据特征的优化器，实现了查询性能的巨大飞跃。
<br />
🎉 3.0.8 版本已于 2025 年 09 月 19
日正式发布，详情可查看[版本发布](../releasenotes/v3.0/release-3.0.8)。从 3.0 版本开始，Apache Doris
除了支持计算存储一体模式外，还支持计算存储分离模式进行集群部署。借助将计算和存储层解耦的云原生架构，用户可以在多个计算集群之间实现查询负载的物理隔离，以及读写负载的隔离。
@@ -26,6 +26,8 @@
<br />
+- [2025-11-24, Apache Doris 3.1.3 版本发布](../releasenotes/v3.1/release-3.1.3.md)
+
- [2025-11-08, Apache Doris 4.0.1 版本发布](../releasenotes/v4.0/release-4.0.1.md)
- [2025-10-27, Apache Doris 3.1.2 版本发布](../releasenotes/v3.1/release-3.1.2.md)
diff --git a/src/constant/version.ts b/src/constant/version.ts
index de901a1f413..c8e01c154d6 100644
--- a/src/constant/version.ts
+++ b/src/constant/version.ts
@@ -1,2 +1,2 @@
export const VERSIONS = ['1.2', '2.0', '2.1', '3.x', '4.x', 'dev'];
-export const DEFAULT_VERSION = '3.x';
+export const DEFAULT_VERSION = '4.x';
diff --git a/versioned_docs/version-2.1/observability/log.md
b/versioned_docs/version-2.1/observability/log.md
index 9455a298c49..6eac7b1d540 100644
--- a/versioned_docs/version-2.1/observability/log.md
+++ b/versioned_docs/version-2.1/observability/log.md
@@ -33,7 +33,7 @@ Before deploying the cluster, you need to estimate the
hardware resources requir
For example, suppose that the daily data increment is 100 TB, the data
compression ratio is 5, the number of data copies is 2, the storage duration of
hot data is 3 days, the storage duration of cold data is 30 days, the ratio of
the peak write throughput to the average write throughput is 200%, the write
throughput of a single-core CUP is 10 MB/s, and 50% of CPU resources are
reserved for data querying, one can estimate that:
-**compute-storage-integerated mode**
+**compute-storage-integrated mode**
- 3 FE servers are required, each configured with a 16-core CPU, 64 GB memory,
and an 1 100 GB SSD disk.
- 30 BE servers are required, each configured with a 32-core CPU, 256 GB
memory, and 8 625 GB SSD disks.
- S3 object storage space 540 TB
diff --git a/versioned_docs/version-3.x/benchmark/tpcds.md
b/versioned_docs/version-3.x/benchmark/tpcds.md
index 164243a8d00..4c280ed73a7 100644
--- a/versioned_docs/version-3.x/benchmark/tpcds.md
+++ b/versioned_docs/version-3.x/benchmark/tpcds.md
@@ -182,7 +182,7 @@ The test results are as follows:
## 6. Environmental Preparation
-Please refer to the [official
document](../../../docs/install/deploy-manually/integrated-storage-compute-deploy-manually)
to install and deploy Doris to obtain a normal running Doris cluster (at least
1 FE 1 BE, 1 FE 3 BE is recommended).
+Please refer to the [official
document](../install/deploy-manually/integrated-storage-compute-deploy-manually)
to install and deploy Doris to obtain a normal running Doris cluster (at least
1 FE 1 BE, 1 FE 3 BE is recommended).
## 7. Data Preparation
diff --git a/versioned_docs/version-3.x/observability/log.md
b/versioned_docs/version-3.x/observability/log.md
index 9455a298c49..6eac7b1d540 100644
--- a/versioned_docs/version-3.x/observability/log.md
+++ b/versioned_docs/version-3.x/observability/log.md
@@ -33,7 +33,7 @@ Before deploying the cluster, you need to estimate the
hardware resources requir
For example, suppose that the daily data increment is 100 TB, the data
compression ratio is 5, the number of data copies is 2, the storage duration of
hot data is 3 days, the storage duration of cold data is 30 days, the ratio of
the peak write throughput to the average write throughput is 200%, the write
throughput of a single-core CUP is 10 MB/s, and 50% of CPU resources are
reserved for data querying, one can estimate that:
-**compute-storage-integerated mode**
+**compute-storage-integrated mode**
- 3 FE servers are required, each configured with a 16-core CPU, 64 GB memory,
and an 1 100 GB SSD disk.
- 30 BE servers are required, each configured with a 32-core CPU, 256 GB
memory, and 8 625 GB SSD disks.
- S3 object storage space 540 TB
diff --git a/versioned_docs/version-3.x/releasenotes/all-release.md
b/versioned_docs/version-3.x/releasenotes/all-release.md
index 3cc4786542e..58cbf8b6607 100644
--- a/versioned_docs/version-3.x/releasenotes/all-release.md
+++ b/versioned_docs/version-3.x/releasenotes/all-release.md
@@ -8,7 +8,7 @@
This document presents a summary of Apache Doris versions released within one
year, listed in reverse chronological order.
:::tip Latest Release
-🎉 Version 3.1.2 is released. Check out the 🔗[Release
Notes](../releasenotes/v3.1/release-3.1.2) here. Doris 3.1 introduces a sparse
column and schema template for the VARIANT data type, making it more efficient
to store and query large datasets with dynamic fields, such as logs and JSON
data. For lakehouse capabilities, it enhances asynchronous materialized views
and expands support for Iceberg and Paimon to build a stronger bridge between
data lakes and data warehouses.
+🎉 Version 3.1.3 is released. Check out the 🔗[Release
Notes](../releasenotes/v3.1/release-3.1.3) here. Doris 3.1 introduces a sparse
column and schema template for the VARIANT data type, making it more efficient
to store and query large datasets with dynamic fields, such as logs and JSON
data. For lakehouse capabilities, it enhances asynchronous materialized views
and expands support for Iceberg and Paimon to build a stronger bridge between
data lakes and data warehouses.
<br />
@@ -23,6 +23,8 @@ This document presents a summary of Apache Doris versions
released within one ye
<br />
+- [2025-11-24, Apache Doris 3.1.3 is
released](../releasenotes/v3.1/release-3.1.3.md)
+
- [2025-10-27, Apache Doris 3.1.2 is
released](../releasenotes/v3.1/release-3.1.2.md)
- [2025-09-26, Apache Doris 3.1.1 is
released](../releasenotes/v3.1/release-3.1.1.md)
diff --git a/versioned_docs/version-4.x/observability/log.md
b/versioned_docs/version-4.x/observability/log.md
index 9455a298c49..6eac7b1d540 100644
--- a/versioned_docs/version-4.x/observability/log.md
+++ b/versioned_docs/version-4.x/observability/log.md
@@ -33,7 +33,7 @@ Before deploying the cluster, you need to estimate the
hardware resources requir
For example, suppose that the daily data increment is 100 TB, the data
compression ratio is 5, the number of data copies is 2, the storage duration of
hot data is 3 days, the storage duration of cold data is 30 days, the ratio of
the peak write throughput to the average write throughput is 200%, the write
throughput of a single-core CUP is 10 MB/s, and 50% of CPU resources are
reserved for data querying, one can estimate that:
-**compute-storage-integerated mode**
+**compute-storage-integrated mode**
- 3 FE servers are required, each configured with a 16-core CPU, 64 GB memory,
and an 1 100 GB SSD disk.
- 30 BE servers are required, each configured with a 32-core CPU, 256 GB
memory, and 8 625 GB SSD disks.
- S3 object storage space 540 TB
diff --git a/versioned_docs/version-4.x/releasenotes/all-release.md
b/versioned_docs/version-4.x/releasenotes/all-release.md
index a2d15b65ad8..5ea5d78f2d3 100644
--- a/versioned_docs/version-4.x/releasenotes/all-release.md
+++ b/versioned_docs/version-4.x/releasenotes/all-release.md
@@ -12,7 +12,7 @@ This document presents a summary of Apache Doris versions
released within one ye
<br />
-🎉 Version 3.1.2 is released. Check out the 🔗[Release
Notes](../releasenotes/v3.1/release-3.1.2) here. Doris 3.1 introduces a sparse
column and schema template for the VARIANT data type, making it more efficient
to store and query large datasets with dynamic fields, such as logs and JSON
data. For lakehouse capabilities, it enhances asynchronous materialized views
and expands support for Iceberg and Paimon to build a stronger bridge between
data lakes and data warehouses.
+🎉 Version 3.1.3 is released. Check out the 🔗[Release
Notes](../releasenotes/v3.1/release-3.1.3) here. Doris 3.1 introduces a sparse
column and schema template for the VARIANT data type, making it more efficient
to store and query large datasets with dynamic fields, such as logs and JSON
data. For lakehouse capabilities, it enhances asynchronous materialized views
and expands support for Iceberg and Paimon to build a stronger bridge between
data lakes and data warehouses.
<br />
@@ -27,6 +27,8 @@ This document presents a summary of Apache Doris versions
released within one ye
<br />
+- [2025-11-24, Apache Doris 3.1.3 is
released](../releasenotes/v3.1/release-3.1.3.md)
+
- [2025-11-08, Apache Doris 4.0.1 is
released](../releasenotes/v4.0/release-4.0.1.md)
- [2025-10-27, Apache Doris 3.1.2 is
released](../releasenotes/v3.1/release-3.1.2.md)
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