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new 4ca2e16eda0 Fix deadlink (#2828)
4ca2e16eda0 is described below
commit 4ca2e16eda05a8d4b8f45d56f559d5e36854fc3c
Author: KassieZ <[email protected]>
AuthorDate: Tue Sep 2 17:43:37 2025 +0800
Fix deadlink (#2828)
## Versions
- [ ] dev
- [ ] 3.0
- [ ] 2.1
- [ ] 2.0
## Languages
- [ ] Chinese
- [ ] English
## Docs Checklist
- [ ] Checked by AI
- [ ] Test Cases Built
---
...is-best-alternatives-for-real-time-analytics.md | 2 +-
docs/admin-manual/cluster-management/fqdn.md | 2 +-
.../trouble-shooting/metadata-operation.md | 2 +-
docs/benchmark/tpcds.md | 2 +-
docs/benchmark/tpch.md | 2 +-
docs/compute-storage-decoupled/overview.md | 2 +-
docs/observability/log.md | 14 ++++++-------
.../data-partitioning/common-issues.md | 2 +-
.../admin-manual/cluster-management/fqdn.md | 4 ++--
.../trouble-shooting/metadata-operation.md | 2 +-
.../current/benchmark/ssb.md | 2 +-
.../current/benchmark/tpcds.md | 2 +-
.../current/benchmark/tpch.md | 2 +-
.../current/compute-storage-decoupled/overview.md | 8 ++++----
.../current/log-storage-analysis.md | 2 +-
.../current/observability/log-storage-analysis.md | 14 ++++++-------
.../current/observability/log.md | 16 +++++++--------
.../current/releasenotes/v2.0/release-2.0.0.md | 2 +-
.../current/releasenotes/v2.1/release-2.1.0.md | 2 +-
.../data-partitioning/common-issues.md | 2 +-
.../version-2.0/ecosystem/beats.md | 14 ++++++-------
.../version-2.0/ecosystem/fluentbit.md | 8 ++++----
.../version-2.0/ecosystem/logstash.md | 16 +++++++--------
.../version-2.0/log-storage-analysis.md | 14 ++++++-------
.../version-2.0/releasenotes/v2.1/release-2.1.0.md | 23 ++++++++++------------
.../admin-manual/cluster-management/fqdn.md | 2 +-
.../version-2.1/log-storage-analysis.md | 4 ++--
.../observability/log-storage-analysis.md | 14 ++++++-------
.../version-2.1/observability/log.md | 16 +++++++--------
.../admin-manual/cluster-management/fqdn.md | 4 ++--
.../version-3.0/log-storage-analysis.md | 4 ++--
.../observability/log-storage-analysis.md | 14 ++++++-------
.../version-3.0/observability/log.md | 16 +++++++--------
versioned_docs/version-2.0/ecosystem/beats.md | 2 +-
versioned_docs/version-2.0/ecosystem/fluentbit.md | 2 +-
versioned_docs/version-2.0/ecosystem/logstash.md | 2 +-
.../practical-guide/log-storage-analysis.md | 14 ++++++-------
.../trouble-shooting/metadata-operation.md | 2 +-
versioned_docs/version-2.1/benchmark/ssb.md | 2 +-
versioned_docs/version-2.1/benchmark/tpcds.md | 2 +-
versioned_docs/version-2.1/benchmark/tpch.md | 2 +-
versioned_docs/version-2.1/log-storage-analysis.md | 2 +-
versioned_docs/version-2.1/observability/log.md | 14 ++++++-------
.../practical-guide/log-storage-analysis.md | 2 +-
.../data-partitioning/common-issues.md | 2 +-
versioned_docs/version-3.0/observability/log.md | 14 ++++++-------
46 files changed, 147 insertions(+), 150 deletions(-)
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 4589bc9c652..a04f3fb4091 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
@@ -413,7 +413,7 @@ Connect with me on
[Linkedin](https://www.linkedin.com/in/kang-xiao-441740316/)
Apache Doris on [GitHub](https://github.com/apache/doris)
-Apache Doris [Website]( https://doris.apache.org)
+Apache Doris [Website](https://doris.apache.org)
diff --git a/docs/admin-manual/cluster-management/fqdn.md
b/docs/admin-manual/cluster-management/fqdn.md
index 7dd8ba109c8..de67166616a 100644
--- a/docs/admin-manual/cluster-management/fqdn.md
+++ b/docs/admin-manual/cluster-management/fqdn.md
@@ -33,7 +33,7 @@ After Doris supports FQDN, communication between nodes is
entirely based on FQDN
```
4. Verification: you can 'ping fe2' on FE1, and can resolve the correct IP
address and ping it, indicating that the network environment is available.
5. fe.conf settings for each FE node ` enable_ fqdn_ mode = true`.
-6. Refer to[Standard
deployment](../../../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually)
+6. Refer to [Standard
deployment](../../install/deploy-manually/integrated-storage-compute-deploy-manually.md)
7. Select several machines to deploy broker on six machines as needed, and
execute `ALTER SYSTEM ADD BROKER broker_name "fe1:8000","be1:8000",...;`.
### Deployment of Doris for K8S
diff --git a/docs/admin-manual/trouble-shooting/metadata-operation.md
b/docs/admin-manual/trouble-shooting/metadata-operation.md
index c679914978c..e826d5b3690 100644
--- a/docs/admin-manual/trouble-shooting/metadata-operation.md
+++ b/docs/admin-manual/trouble-shooting/metadata-operation.md
@@ -267,7 +267,7 @@ The third level can display the value information of the
specified key.
## Best Practices
-The deployment recommendation of FE is described in the Installation and
[Deployment
Document](../../../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually).
Here are some supplements.
+The deployment recommendation of FE is described in the Installation and
[Deployment
Document](../../install/deploy-manually/integrated-storage-compute-deploy-manually.md).
Here are some supplements.
* **If you don't know the operation logic of FE metadata very well, or you
don't have enough experience in the operation and maintenance of FE metadata,
we strongly recommend that only one FOLLOWER-type FE be deployed as MASTER in
practice, and the other FEs are OBSERVER, which can reduce many complex
operation and maintenance problems.** Don't worry too much about the failure of
MASTER single point to write metadata. First, if you configure it properly, FE
as a java process is very diff [...]
diff --git a/docs/benchmark/tpcds.md b/docs/benchmark/tpcds.md
index 352fe2d96d7..2b21e96146a 100644
--- a/docs/benchmark/tpcds.md
+++ b/docs/benchmark/tpcds.md
@@ -181,7 +181,7 @@ The test results are as follows: (Apache Doris 2.0.15.1 q78
q79 failed to execut
## 6. Environmental Preparation
-Please refer to the [official
document](../../versioned_docs/version-2.1/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.md)
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/docs/benchmark/tpch.md b/docs/benchmark/tpch.md
index e5d86260664..77d827ea085 100644
--- a/docs/benchmark/tpch.md
+++ b/docs/benchmark/tpch.md
@@ -86,7 +86,7 @@ Here we use Apache Doris 2.1.7-rc03 and Apache Doris 2.0.15.1
for comparative te
## 6. Environmental Preparation
-Please refer to the [official
document](../../versioned_docs/version-2.1/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.md)
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/docs/compute-storage-decoupled/overview.md
b/docs/compute-storage-decoupled/overview.md
index ca77326580a..1b34983eb81 100644
--- a/docs/compute-storage-decoupled/overview.md
+++ b/docs/compute-storage-decoupled/overview.md
@@ -7,7 +7,7 @@
This article introduces the differences, advantages, and applicable scenarios
of the compute-storage coupled mode and compute-storage decoupled mode of
Doris, providing a reference for users' selection.
-The following sections will describe in detail how to deploy and use Apache
Doris in the compute-storage decoupled mode. For information on deployment in
compute-storage coupled mode, please refer to the [Cluster
Deployment](../../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually)
section.
+The following sections will describe in detail how to deploy and use Apache
Doris in the compute-storage decoupled mode. For information on deployment in
compute-storage coupled mode, please refer to the [Cluster
Deployment](../install/deploy-manually/integrated-storage-compute-deploy-manually.md)
section.
## **Compute-storage coupled VS decoupled**
diff --git a/docs/observability/log.md b/docs/observability/log.md
index 45b32f11027..bac7f33066b 100644
--- a/docs/observability/log.md
+++ b/docs/observability/log.md
@@ -70,7 +70,7 @@ Refer to the following table to learn about the values of
indicators in the exam
## Step 2: Deploy the cluster
-After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually).
+After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../install/deploy-manually/integrated-storage-compute-deploy-manually.md).
## Step 3: Optimize FE and BE configurations
@@ -90,7 +90,7 @@ You can find FE configuration fields in `fe/conf/fe.conf`.
Refer to the followin
| `autobucket_min_buckets = 10` | Increase the
minimum number of automatically bucketed buckets from 1 to 10 to avoid
insufficient buckets when the log volume increases. |
| `max_backend_heartbeat_failure_tolerance_count = 10` | In log
scenarios, the BE server may experience high pressure, leading to short-term
timeouts, so increase the tolerance count from 1 to 10. |
-For more information, refer to [FE
Configuration](./admin-manual/config/fe-config.md).
+For more information, refer to [FE
Configuration](../admin-manual/config/fe-config.md).
**Optimize BE configurations**
@@ -119,7 +119,7 @@ You can find BE configuration fields in `be/conf/be.conf`.
Refer to the followin
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
Accelerate the recycling of trash files. |
-For more information, refer to [BE
Configuration](./admin-manual/config/be-config).
+For more information, refer to [BE
Configuration](../admin-manual/config/be-config).
### Step 4: Create tables
@@ -129,7 +129,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- For data partitioning:
- - Enable [range
partitioning](./table-design/data-partitioning/manual-partitioning.md#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](./table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
+ - Enable [range
partitioning](../table-design/data-partitioning/manual-partitioning.md#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](../table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
- Use a field in the DATETIME type as the sort key (`DUPLICATE KEY(ts)`)
for accelerated retrieval of the latest N log entries.
@@ -139,7 +139,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- Use the Random strategy (`DISTRIBUTED BY RANDOM BUCKETS 60`) to optimize
batch writing efficiency when paired with single tablet imports.
-For more information, refer to [Data
Partitioning](./table-design/data-partitioning/auto-partitioning).
+For more information, refer to [Data
Partitioning](../table-design/data-partitioning/auto-partitioning).
**Configure compression parameters**
@@ -294,7 +294,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../../ecosystem/logstash.md).
+For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../ecosystem/logstash.md).
**Integrating Filebeat**
@@ -362,7 +362,7 @@ headers:
./filebeat-doris-7.17.5.4 -c filebeat_demo.yml
```
-For more information about Filebeat, refer to [Beats Doris Output
Plugin](../../ecosystem/beats.md).
+For more information about Filebeat, refer to [Beats Doris Output
Plugin](../ecosystem/beats.md).
**Integrating Kafka**
diff --git a/docs/table-design/data-partitioning/common-issues.md
b/docs/table-design/data-partitioning/common-issues.md
index ed2dacb0166..ffde1557641 100644
--- a/docs/table-design/data-partitioning/common-issues.md
+++ b/docs/table-design/data-partitioning/common-issues.md
@@ -20,7 +20,7 @@
- In the fe.log, search for the `Failed to create partition` log entry at
the corresponding timestamp. In this log entry, you may find a series of number
pairs similar to `{10001-10010}`. The first number in the pair represents the
Backend ID, and the second number represents the Tablet ID. For example, this
number pair indicates that the creation of Tablet ID 10010 on Backend ID 10001
failed.
- Go to the be.INFO log of the corresponding Backend and search for Tablet
ID-related logs within the corresponding time period to find error messages.
- Here are some common tablet creation failure errors, including but not
limited to:
- - The BE did not receive the relevant task. In this case, you cannot find
Tablet ID-related logs in be.INFO or the BE reports success but actually fails.
For these issues, please refer to the [Installation and
Deployment](../../../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually)
section to check the connectivity between FE and BE.
+ - The BE did not receive the relevant task. In this case, you cannot find
Tablet ID-related logs in be.INFO or the BE reports success but actually fails.
For these issues, please refer to the [Installation and
Deployment](../../install/deploy-manually/integrated-storage-compute-deploy-manually.md)
section to check the connectivity between FE and BE.
- Pre-allocated memory failure. This may be because the byte length of a
row in the table exceeds 100KB.
- `Too many open files`. The number of open file handles exceeds the
Linux system limit. You need to modify the handle limit of the Linux system.
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/cluster-management/fqdn.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/cluster-management/fqdn.md
index c0ece8f0877..e190444316c 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/cluster-management/fqdn.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/cluster-management/fqdn.md
@@ -43,7 +43,7 @@ Doris 支持 FQDN 之后，各节点之间通信完全基于 FQDN。添加各类
5. 每个 FE 节点的 fe.conf 设置 `enable_fqdn_mode = true`。
-6.
参考[手动部署](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
+6.
参考[手动部署](../../install/deploy-manually/integrated-storage-compute-deploy-manually)
7. 按需在六台机器上选择几台机器部署 broker，执行`ALTER SYSTEM ADD BROKER broker_name
"fe1:8000","be1:8000",...;`。
@@ -51,7 +51,7 @@ Doris 支持 FQDN 之后，各节点之间通信完全基于 FQDN。添加各类
Pod 意外重启后，K8s 不能保证 Pod 的 IP 不发生变化，但是能保证域名不变，基于这一特性，Doris 开启 FQDN 时，能保证 Pod
意外重启后，还能正常提供服务。
-K8s 部署 Doris 的方法请参考[K8s 部署
Doris](../../../version-3.0/install/deploy-on-kubernetes/integrated-storage-compute/install-doris-cluster)
+K8s 部署 Doris 的方法请参考[K8s 部署
Doris](../../install/deploy-on-kubernetes/integrated-storage-compute/install-doris-cluster)
### 服务器变更 IP
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/trouble-shooting/metadata-operation.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/trouble-shooting/metadata-operation.md
index 688231e1591..d0b2a2ec4f3 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/trouble-shooting/metadata-operation.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/admin-manual/trouble-shooting/metadata-operation.md
@@ -267,7 +267,7 @@ mysql> show proc "/bdbje/110589/114861";
## 最佳实践
-FE 的部署推荐，在
[安装与部署文档](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
中有介绍，这里再做一些补充。
+FE 的部署推荐，在
[安装与部署文档](../../install/deploy-manually/integrated-storage-compute-deploy-manually)
中有介绍，这里再做一些补充。
* **如果你并不十分了解 FE 元数据的运行逻辑，或者没有足够 FE 元数据的运维经验，我们强烈建议在实际使用中，只部署一个 FOLLOWER 类型的
FE 作为 MASTER，其余 FE 都是 OBSERVER，这样可以减少很多复杂的运维问题！** 不用过于担心 MASTER
单点故障导致无法进行元数据写操作。首先，如果你配置合理，FE 作为 java 进程很难挂掉。其次，如果 MASTER 磁盘损坏（概率非常低），我们也可以用
OBSERVER 上的元数据，通过 `元数据恢复模式` 的方式手动恢复。
diff --git a/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/ssb.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/ssb.md
index acb31635cef..b21ae22273e 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/ssb.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/ssb.md
@@ -85,7 +85,7 @@
## 6. 环境准备
-请先参照
[官方文档](../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
进行 Apache Doris 的安装部署，以获得一个正常运行中的 Doris 集群（至少包含 1 FE 1 BE，推荐 1 FE 3 BE）。
+请先参照
[官方文档](../install/deploy-manually/integrated-storage-compute-deploy-manually)
进行 Apache Doris 的安装部署，以获得一个正常运行中的 Doris 集群（至少包含 1 FE 1 BE，推荐 1 FE 3 BE）。
## 7. 数据准备
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpcds.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpcds.md
index 162e1002fd1..daa5e4b8e8e 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpcds.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpcds.md
@@ -179,7 +179,7 @@ TPC-DS 99 个测试查询语句：
[TPC-DS-Query-SQL](https://github.com/apache/
## 6. 环境准备
-请先参照
[官方文档](../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
进行 Doris 的安装部署，以获得一个正常运行中的 Doris 集群（至少包含 1 FE 1 BE，推荐 1 FE 3 BE）。
+请先参照
[官方文档](../install/deploy-manually/integrated-storage-compute-deploy-manually)
进行 Doris 的安装部署，以获得一个正常运行中的 Doris 集群（至少包含 1 FE 1 BE，推荐 1 FE 3 BE）。
## 7. 数据准备
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpch.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpch.md
index 85270503882..0598e854d97 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpch.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/benchmark/tpch.md
@@ -84,7 +84,7 @@ TPC-H 22 个测试查询语句：
[TPCH-Query-SQL](https://github.com/apache/dor
## 6. 环境准备
-请先参照
[官方文档](../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
进行 Doris 的安装部署，以获得一个正常运行中的 Doris 集群（至少包含 1 FE 1 BE，推荐 1 FE 3 BE）。
+请先参照
[官方文档](../install/deploy-manually/integrated-storage-compute-deploy-manually)
进行 Doris 的安装部署，以获得一个正常运行中的 Doris 集群（至少包含 1 FE 1 BE，推荐 1 FE 3 BE）。
## 7. 数据准备
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/compute-storage-decoupled/overview.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/compute-storage-decoupled/overview.md
index b802f20bf88..b5180d017df 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/compute-storage-decoupled/overview.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/compute-storage-decoupled/overview.md
@@ -5,7 +5,7 @@
}
---
-本文介绍存算分离与存算一体两种架构的区别、优势和适用场景，为用户的选择与使用提供参考。后文将详细说明如何部署并使用 Apache Doris
存算分离模式。如需部署存算一体模式，请参考[集群部署](../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+本文介绍存算分离与存算一体两种架构的区别、优势和适用场景，为用户的选择与使用提供参考。后文将详细说明如何部署并使用 Apache Doris
存算分离模式。如需部署存算一体模式，请参考[集群部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
## 存算一体 VS 存算分离
@@ -41,7 +41,7 @@ Meta Service 是 Doris 存算分离元数据服务，主要负责处理导入事
### 存算分离的限制
-当前版本Doris存算分离模式还不支持CCR，备份恢复功能，这些功能在持续迭代中，后续版本会陆续支持。
+当前版本 Doris 存算分离模式还不支持 CCR，备份恢复功能，这些功能在持续迭代中，后续版本会陆续支持。
## 如何选择
@@ -67,8 +67,8 @@ Meta Service 是 Doris 存算分离元数据服务，主要负责处理导入事
- 已在使用公有云服务
- 具备可靠的高性能共享存储系统[1]，比如 HDFS、Ceph、对象存储等
-- 多个业务使用共享同一份数据, 并且有隔离计算的需求
+- 多个业务使用共享同一份数据，并且有隔离计算的需求
- 需要极致的弹性扩缩容，需要 K8S 容器化，需要运行在私有云上
- 有专职团队维护整个公司的数据仓库平台
-[1] 如果共享存储的吞吐或者延迟等性能比较差，对于存算分离架构Doris有比较大的性能影响。
+[1] 如果共享存储的吞吐或者延迟等性能比较差，对于存算分离架构 Doris 有比较大的性能影响。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/log-storage-analysis.md
index c260e064fc7..9317caeca9d 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/log-storage-analysis.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/log-storage-analysis.md
@@ -133,7 +133,7 @@ Apache Doris 对 Flexible Schema 的日志数据提供了几个方面的支持
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](./install/deploy-manually/integrated-storage-compute-deploy-manually)。
### 第 3 步：优化 FE 和 BE 配置
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log-storage-analysis.md
index 0a9d75d40b4..0d3e9d56585 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log-storage-analysis.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log-storage-analysis.md
@@ -51,7 +51,7 @@
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
### 第 3 步：优化 FE 和 BE 配置
@@ -70,7 +70,7 @@
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](../admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -98,7 +98,7 @@
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](../admin-manual/config/be-config)。
### 第 4 步：建表
@@ -107,14 +107,14 @@
**配置分区分桶参数**
分区时，按照以下说明配置：
-- 使用时间字段上的 [Range
分区](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- 使用时间字段上的 [Range
分区](../table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](../table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶时，按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考 [数据划分](../table-design/data-partitioning/data-distribution)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -265,7 +265,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../ecosystem/logstash)。
**对接 Filebeat**
@@ -341,7 +341,7 @@ chmod +x filebeat-doris-1.0.0
./filebeat-doris-1.0.0 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../ecosystem/beats)。
**对接 Kafka**
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log.md
index ee801ae0c82..3458bbcd78c 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/current/observability/log.md
@@ -54,7 +54,7 @@ under the License.
- BE：15 台服务器，每台配置 32 核 CPU、256 GB 内存、8 块 680 GB SSD 盘
- S3 对象存储空间：即为预估冷数据存储空间，600 TB
-使用存算分离模式，写入和热数据存储只需要 1副本，能够显著降低成本。
+使用存算分离模式，写入和热数据存储只需要 1 副本，能够显著降低成本。
该例子中，各关键指标的值及具体计算方法可见下表：
@@ -80,7 +80,7 @@ under the License.
## 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
## 第 3 步：优化 FE 和 BE 配置
@@ -99,7 +99,7 @@ under the License.
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](../admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -127,7 +127,7 @@ under the License.
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](../admin-manual/config/be-config)。
### 第 4 步：建表
@@ -136,14 +136,14 @@ under the License.
**配置分区分桶参数**
分区按照以下说明配置：
-- 使用时间字段上的 [Range
分区](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- 使用时间字段上的 [Range
分区](../table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](../table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为排序 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考 [数据划分](../table-design/data-partitioning/data-distribution)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -295,7 +295,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../ecosystem/logstash)。
**对接 Filebeat**
@@ -371,7 +371,7 @@ chmod +x filebeat-doris-7.17.5.4
./filebeat-doris-7.17.5.4 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../ecosystem/beats)。
**对接 Kafka**
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.0/release-2.0.0.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.0/release-2.0.0.md
index a8c0530e81f..dde2b305e25 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.0/release-2.0.0.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.0/release-2.0.0.md
@@ -50,7 +50,7 @@
在实现极速分析体验的同时，为了保证多个混合分析负载的执行效率以及查询的稳定性，在 2.0.0 版本中我们引入了 Pipeline
执行模型作为查询执行引擎。在 Pipeline 执行引擎中，查询的执行是由数据来驱动控制流变化的，各个查询执行过程之中的阻塞算子被拆分成不同
Pipeline，各个 Pipeline
能否获取执行线程调度执行取决于前置数据是否就绪，实现了阻塞操作的异步化、可以更加灵活地管理系统资源，同时减少了线程频繁创建和销毁带来的开销，并提升了
Apache Doris 对于 CPU 的利用效率。因此 Apache Doris 在混合负载场景中的查询性能和稳定性都得到了全面提升。
-参考文档：[查询执行引擎](../../query-acceleration/optimization-technology-principle/pipeline-execution-engine)
+参考文档：[查询执行引擎](../../query-acceleration/optimization-technology-principle/pipeline-execution-engine.md)
如何开启：` Set enable_pipeline_engine = true `
- 该功能在 Apache Doris 2.0 版本中将默认开启，BE 在进行查询执行时默认将 SQL 的执行模型转变 Pipeline 的执行方式。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.1/release-2.1.0.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.1/release-2.1.0.md
index 38f19d02682..c8a833115d0 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.1/release-2.1.0.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/releasenotes/v2.1/release-2.1.0.md
@@ -84,7 +84,7 @@
:::note 备注
-参考文档：[Pipeline X
执行引擎](../../query-acceleration/optimization-technology-principle/pipeline-execution-engine)
+参考文档：[Pipeline X
执行引擎](../../query-acceleration/optimization-technology-principle/pipeline-execution-engine.md)
:::
## ARM 架构深度适配，性能提升 230%
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/table-design/data-partitioning/common-issues.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/table-design/data-partitioning/common-issues.md
index 550475debf3..a2899a6e481 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/current/table-design/data-partitioning/common-issues.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/current/table-design/data-partitioning/common-issues.md
@@ -25,7 +25,7 @@ Doris 建表是按照 Partition 粒度依次创建的。当一个 Partition 创
- 以下罗列一些常见的 tablet 创建失败错误，包括但不限于：
- - BE 没有收到相关 task，此时无法在 be.INFO 中找到 tablet id 相关日志或者 BE
创建成功，但汇报失败。以上问题，请参阅
[安装与部署](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
检查 FE 和 BE 的连通性。
+ - BE 没有收到相关 task，此时无法在 be.INFO 中找到 tablet id 相关日志或者 BE
创建成功，但汇报失败。以上问题，请参阅
[安装与部署](../../install/deploy-manually/integrated-storage-compute-deploy-manually)
检查 FE 和 BE 的连通性。
- 预分配内存失败。可能是表中一行的字节长度超过了 100KB。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/beats.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/beats.md
index 1e12f1453b4..ee4d50557bd 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/beats.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/beats.md
@@ -11,10 +11,10 @@
Beats Doris output plugin 支持
[Filebeat](https://github.com/elastic/beats/tree/master/filebeat),
[Metricbeat](https://github.com/elastic/beats/tree/master/metricbeat),
[Packetbeat](https://github.com/elastic/beats/tree/master/packetbeat),
[Winlogbeat](https://github.com/elastic/beats/tree/master/winlogbeat),
[Auditbeat](https://github.com/elastic/beats/tree/master/auditbeat),
[Heartbeat](https://github.com/elastic/beats/tree/master/heartbeat) 。
-Beats Doris output plugin 调用 [Doris Stream
Load](../data-operate/import/import-way/stream-load-manual) HTTP 接口将数据实时写入
Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。
+Beats Doris output plugin 调用 [Doris Stream
Load](../data-operate/import/stream-load-manual.md) HTTP 接口将数据实时写入
Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。
使用 Beats Doris output plugin 主要有三个步骤：
-1. 下载或编译包含 Doris output plugin 的 Beats二进制程序
+1. 下载或编译包含 Doris output plugin 的 Beats 二进制程序
2. 配置 Beats 输出地址和其他参数
3. 启动 Beats 将数据实时写入 Doris
@@ -47,15 +47,15 @@ Beats Doris output plugin 的配置如下：
配置 | 说明
--- | ---
-`http_hosts` | Stream Load HTTP 地址，格式是字符串数组，可以有一个或者多个元素，每个元素是 host:port。
例如：["http://fe1:8030";, "http://fe2:8030";]
-`user` | Doris 用户名，该用户需要有doris对应库表的导入权限
+`http_hosts` | Stream Load HTTP 地址，格式是字符串数组，可以有一个或者多个元素，每个元素是
host:port。例如：["http://fe1:8030";, "http://fe2:8030";]
+`user` | Doris 用户名，该用户需要有 doris 对应库表的导入权限
`password` | Doris 用户的密码
`database` | 要写入的 Doris 库名
`table` | 要写入的 Doris 表名
`label_prefix` | Doris Stream Load Label 前缀，最终生成的 Label 为
*{label_prefix}_{db}_{table}_{yyyymmdd_hhmmss}_{uuid}* ，默认值是 beats
`headers` | Doris Stream Load 的 headers 参数，语法格式为 YAML map
-`codec_format_string` | 输出到 Doris Stream Load 的format string，%{[a][b]} 代表输入中的
a.b 字段，参考后续章节的使用示例
-`bulk_max_size` | Doris Stream Load 的 batch size，默认为100000
+`codec_format_string` | 输出到 Doris Stream Load 的 format string，%{[a][b]} 代表输入中的
a.b 字段，参考后续章节的使用示例
+`bulk_max_size` | Doris Stream Load 的 batch size，默认为 100000
`max_retries` | Doris Stream Load 请求失败重试次数，默认为 -1 无限重试保证数据可靠性
`log_request` | 日志中是否输出 Doris Stream Load 请求和响应元数据，用于排查问题，默认为 true
`log_progress_interval` | 日志中输出速度的时间间隔，单位是秒，默认为 10，设置为 0 可以关闭这种日志
@@ -230,7 +230,7 @@ total 11 MB 18978 ROWS, total speed 0 MB/s 632 R/s, last 10
seconds speed 1 MB/s
**1. 数据**
-github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从
https://www.gharchive.org/ 下载，比如下载 2024年1月1日15点的数据。
+github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从
https://www.gharchive.org/ 下载，比如下载 2024 年 1 月 1 日 15 点的数据。
```
wget https://data.gharchive.org/2024-01-01-15.json.gz
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/fluentbit.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/fluentbit.md
index 0fd63c9f55c..98df84486e3 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/fluentbit.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/fluentbit.md
@@ -7,7 +7,7 @@
[Fluent Bit](https://fluentbit.io/) 是一个快速的日志处理器和转发器，它支持自定义输出插件将数据写入存储系统，Fluent
Bit Doris Output Plugin 是输出到 Doris 的插件。
-Fluent Bit Doris Output Plugin 调用 [Doris Stream
Load](../data-operate/import/import-way/stream-load-manual) HTTP 接口将数据实时写入
Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。
+Fluent Bit Doris Output Plugin 调用 [Doris Stream
Load](../data-operate/import/stream-load-manual.md) HTTP 接口将数据实时写入
Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。
使用 Fluent Bit Doris Output Plugin 主要有三个步骤：
1. 下载或编译包含 Doris Output Plugin 的 Fluent Bit 二进制程序
@@ -39,12 +39,12 @@ Fluent Bit Doris output plugin 的配置如下：
--- | ---
`host` | Stream Load HTTP host
`port` | Stream Load HTTP port
-`user` | Doris 用户名，该用户需要有doris对应库表的导入权限
+`user` | Doris 用户名，该用户需要有 doris 对应库表的导入权限
`password` | Doris 用户的密码
`database` | 要写入的 Doris 库名
`table` | 要写入的 Doris 表名
`label_prefix` | Doris Stream Load Label 前缀，最终生成的 Label 为
*{label_prefix}\_{timestamp}\_{uuid}* ，默认值是 fluentbit, 如果设置为 false 则不会添加 Label
- `time_key` | 数据中要添加的时间戳列的名称，默认值是 date， 如果设置为 false 则不会添加该列
+ `time_key` | 数据中要添加的时间戳列的名称，默认值是 date，如果设置为 false 则不会添加该列
`header` | Doris Stream Load 的 header 参数，可以设置多个
`log_request` | 日志中是否输出 Doris Stream Load 请求和响应元数据，用于排查问题，默认为 true
`log_progress_interval` | 日志中输出速度的时间间隔，单位是秒，默认为 10，设置为 0 可以关闭这种日志
@@ -231,7 +231,7 @@ fluent-bit -c doris_log.conf
**1. 数据**
-github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从
https://www.gharchive.org/ 下载，比如下载 2024年1月1日15点的数据。
+github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从
https://www.gharchive.org/ 下载，比如下载 2024 年 1 月 1 日 15 点的数据。
```shell
wget https://data.gharchive.org/2024-01-01-15.json.gz
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/logstash.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/logstash.md
index c2b6941a042..7f17abf28a0 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/logstash.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/ecosystem/logstash.md
@@ -9,9 +9,9 @@
## 介绍
-Logstash 是一个日志ETL框架（采集，预处理，发送到存储系统），它支持自定义输出插件将数据写入存储系统，Logstash Doris output
plugin 是输出到 Doris 的插件。
+Logstash 是一个日志 ETL 框架（采集，预处理，发送到存储系统），它支持自定义输出插件将数据写入存储系统，Logstash Doris
output plugin 是输出到 Doris 的插件。
-Logstash Doris output plugin 调用 [Doris Stream
Load](../data-operate/import/import-way/stream-load-manual) HTTP 接口将数据实时写入
Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。
+Logstash Doris output plugin 调用 [Doris Stream
Load](../data-operate/import/stream-load-manual.md) HTTP 接口将数据实时写入
Doris，提供多线程并发，失败重试，自定义 Stream Load 格式和参数，输出写入速度等能力。
使用 Logstash Doris output plugin 主要有三个步骤：
1. 将插件安装到 Logstash 中
@@ -51,7 +51,7 @@ Installing logstash-output-doris
Installation successful
```
-普通安装模式会自动安装插件依赖的 ruby 模块，对于网络不通的情况会卡住无法完成，这种情况下可以下载包含依赖的zip安装包进行完全离线安装，注意需要用
file:// 指定本地文件系统。
+普通安装模式会自动安装插件依赖的 ruby 模块，对于网络不通的情况会卡住无法完成，这种情况下可以下载包含依赖的 zip 安装包进行完全离线安装，注意需要用
file:// 指定本地文件系统。
- 离线安装
@@ -69,14 +69,14 @@ Logstash Doris output plugin 的配置如下：
配置 | 说明
--- | ---
-`http_hosts` | Stream Load HTTP 地址，格式是字符串数组，可以有一个或者多个元素，每个元素是 host:port。
例如：["http://fe1:8030";, "http://fe2:8030";]
-`user` | Doris 用户名，该用户需要有doris对应库表的导入权限
+`http_hosts` | Stream Load HTTP 地址，格式是字符串数组，可以有一个或者多个元素，每个元素是
host:port。例如：["http://fe1:8030";, "http://fe2:8030";]
+`user` | Doris 用户名，该用户需要有 doris 对应库表的导入权限
`password` | Doris 用户的密码
`db` | 要写入的 Doris 库名
`table` | 要写入的 Doris 表名
`label_prefix` | Doris Stream Load Label 前缀，最终生成的 Label 为
*{label_prefix}_{db}_{table}_{yyyymmdd_hhmmss}_{uuid}* ，默认值是 logstash
`headers` | Doris Stream Load 的 headers 参数，语法格式为 ruby map，例如：headers => {
"format" => "json" "read_json_by_line" => "true" }
-`mapping` | Logstash 字段到 Doris 表字段的映射， 参考后续章节的使用示例
+`mapping` | Logstash 字段到 Doris 表字段的映射，参考后续章节的使用示例
`message_only` | 一种特殊的 mapping 形式，只将 Logstash 的 @message 字段输出到 Doris，默认为 false
`max_retries` | Doris Stream Load 请求失败重试次数，默认为 -1 无限重试保证数据可靠性
`log_request` | 日志中是否输出 Doris Stream Load 请求和响应元数据，用于排查问题，默认为 false
@@ -145,7 +145,7 @@ PROPERTIES (
Logstash 主要有两类配置文件，一类是整个 Logstash 的配置文件，另一类是某个日志采集的配置文件。
-整个 Logstash 的配置文件通常在 config/logstash.yml，为了提升写入 Doris 的性能需要修改 batch
大小和攒批时间，对于平均每条i几百字节的日志，推荐 100 万行和 10s 。
+整个 Logstash 的配置文件通常在 config/logstash.yml，为了提升写入 Doris 的性能需要修改 batch
大小和攒批时间，对于平均每条 i 几百字节的日志，推荐 100 万行和 10s。
```
pipeline.batch.size: 1000000
pipeline.batch.delay: 10000
@@ -258,7 +258,7 @@ ${LOGSTASH_HOME}/bin/logstash -f
config/logstash_doris_log.conf
**1. 数据**
-github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从
https://www.gharchive.org/ 下载，比如下载 2024年1月1日15点的数据。
+github events archive 是 github 用户操作事件的归档数据，格式是 JSON，可以从
https://www.gharchive.org/ 下载，比如下载 2024 年 1 月 1 日 15 点的数据。
```
wget https://data.gharchive.org/2024-01-01-15.json.gz
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/log-storage-analysis.md
index d0a9e0ddedd..0d48a8022bc 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/log-storage-analysis.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/log-storage-analysis.md
@@ -133,7 +133,7 @@ Apache Doris 对 Flexible Schema 的日志数据提供了几个方面的支持
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../../install/cluster-deployment/standard-deployment)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](./install/cluster-deployment/standard-deployment)。
### 第 3 步：优化 FE 和 BE 配置
@@ -152,7 +152,7 @@ Apache Doris 对 Flexible Schema 的日志数据提供了几个方面的支持
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](../../admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -180,7 +180,7 @@ Apache Doris 对 Flexible Schema 的日志数据提供了几个方面的支持
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](../../admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
### 第 4 步：建表
@@ -189,14 +189,14 @@ Apache Doris 对 Flexible Schema 的日志数据提供了几个方面的支持
**配置分区分桶参数**
分区时，按照以下说明配置：
-- 使用时间字段上的 (./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- [使用时间字段上的](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶时，按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考
[数据划分](./table-design/data-partitioning/manual-partitioning.md)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -347,7 +347,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../../ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
**对接 Filebeat**
@@ -423,7 +423,7 @@ chmod +x filebeat-doris-1.0.0
./filebeat-doris-1.0.0 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../../ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
**对接 Kafka**
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/releasenotes/v2.1/release-2.1.0.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/releasenotes/v2.1/release-2.1.0.md
index 4a44ab4defa..0ea42e984d7 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/releasenotes/v2.1/release-2.1.0.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.0/releasenotes/v2.1/release-2.1.0.md
@@ -84,7 +84,7 @@
:::note 备注
-参考文档：[Pipeline X
执行引擎](../../query-acceleration/optimization-technology-principle/pipeline-execution-engine)
+参考文档：[Pipeline X 执行引擎](../../query/pipeline-execution-engine.md)
:::
## ARM 架构深度适配，性能提升 230%
@@ -123,7 +123,7 @@
:::note
- [演示
Demo](https://www.bilibili.com/video/BV1cS421A7kA/?spm_id_from=333.999.0.0)
-- 参考文档：[SQL 方言兼容](../../lakehouse/sql-dialect.md)
+- 参考文档：[SQL
方言兼容](https://doris.apache.org/docs/3.0/lakehouse/sql-convertor/sql-convertor-overview)
:::
@@ -282,7 +282,7 @@ CREATE MATERIALIZED VIEW mv1
:::note
- 演示 Demo: https://www.bilibili.com/video/BV1s2421T71z/?spm_id_from=333.999.0.0
--
参考文档：[异步物化视图](../../query-acceleration/materialized-view/async-materialized-view/overview)
+- 参考文档：[异步物化视图](../../query/view-materialized-view/materialized-view.md)
:::
## 存储能力增强
@@ -388,7 +388,7 @@ PROPERTIES (
:::note
-参考文档：[数据划分](./table-design/data-partitioning/data-distribution)
+参考文档：[数据划分](../../table-design/data-partitioning/manual-partitioning.md)
:::
### INSERT INTO SELECT 导入性能提升 100%
@@ -450,7 +450,7 @@ MemTable 前移在 2.1 版本中默认开启，用户无需修改原有的导入
:::note
- 演示 Demo：https://www.bilibili.com/video/BV1um411o7Ha/?spm_id_from=333.999.0.0
-- 参考文档和完整测试报告：[Group Commit](../../data-operate/import/group-commit-manual)
+- 参考文档和完整测试报告：[Group
Commit](https://doris.apache.org/docs/2.1/data-operate/import/group-commit-manual)
:::
@@ -522,7 +522,7 @@ SELECT v["properties"]["title"] from ${table_name}
:::note
- 演示 Demo: https://www.bilibili.com/video/BV13u4m1g7ra/?spm_id_from=333.999.0.0
-- 参考文档：[VARIANT](../../sql-manual/sql-data-types/semi-structured/VARIANT.md)
+-
参考文档：[VARIANT](https://doris.apache.org/docs/2.1/sql-manual/basic-element/sql-data-types/semi-structured/VARIANT)
:::
@@ -536,10 +536,7 @@ SELECT v["properties"]["title"] from ${table_name}
- IPV4_CIDR_TO_RANGE：接收一个 IPv4 和一个包含 CIDR 的 Int16 值，返回一个结构体，其中包含两个 IPv4
字段分别表示子网的较低范围（min）和较高范围（max）；
- INET_ATON：获取包含 IPv4 地址的字符串，格式为 A.B.C.D（点分隔的十进制数字）
-:::note
-参考文档：[IPV6](../../sql-manual/sql-data-types/ip/IPV6)
-:::
### 复杂数据类型分析函数完善
@@ -679,14 +676,14 @@ mysql> select struct(1,"2") not in (struct(1,3),
struct(1,"2"), struct(1,1), nul
:::note
- 演示 Demo：https://www.bilibili.com/video/BV1Fz421X7XE/?spm_id_from=333.999.0.0
-- 参考文档：[Workload Group](../../admin-manual/workload-management/workload-group)
+- 参考文档：[Workload Group](../../admin-manual/resource-admin/workload-group.md)
:::
### TopSQL
:::tip
-自 2.1.1 版本之后，active_queries() 已经废弃，TopSQl 主要通过 Doris 内置的系统表实现，参考文档
[工作负载诊断与分析](../../admin-manual/workload-management/analysis-diagnosis.md)
+自 2.1.1 版本之后，active_queries() 已经废弃，TopSQl 主要通过 Doris 内置的系统表实现，参考文档
[工作负载诊断与分析](https://doris.apache.org/docs/2.1/admin-manual/workload-management/analysis-diagnosis)
:::
当集群出现预期外的大查询导致集群整体负载上升、查询可用性下降时，用户难以快速找到这些大查询并进行相应的降级操作。因此在 Apache Doris 2.1
版本中我们支持了运行时查看 SQL 资源用量的功能，具体指标如下：
@@ -741,7 +738,7 @@ select QueryId,max(BePeakMemoryBytes) as be_peak_mem from
active_queries() group
目前主要展示的负载类型包括 Select 和`Insert Into……Select`，预计在 2.1 版本之上的三位迭代版本中会支持 Stream
Load 和 Broker Load 的资源用量展示。
:::note
-参考文档：[ACTIVE_QUERIES](../../admin-manual/system-tables/information_schema/active_queries)
+参考文档：[ACTIVE_QUERIES](https://doris.apache.org/docs/2.1/admin-manual/system-tables/information_schema/active_queries)
:::
@@ -842,7 +839,7 @@ JOB e_daily
:::caution 注意事项
-当前 Job Scheduler 仅支持 Insert
内表，参考文档：[CREATE-JOB](../../sql-manual/sql-statements/job/CREATE-JOB)
+当前 Job Scheduler 仅支持 Insert
内表，参考文档：[CREATE-JOB](https://doris.apache.org/docs/2.1/sql-manual/sql-statements/job/CREATE-JOB)
:::
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/admin-manual/cluster-management/fqdn.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/admin-manual/cluster-management/fqdn.md
index c0ece8f0877..b049d5c227e 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/admin-manual/cluster-management/fqdn.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/admin-manual/cluster-management/fqdn.md
@@ -43,7 +43,7 @@ Doris 支持 FQDN 之后，各节点之间通信完全基于 FQDN。添加各类
5. 每个 FE 节点的 fe.conf 设置 `enable_fqdn_mode = true`。
-6.
参考[手动部署](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
+6.
参考[手动部署](../../install/deploy-manually/integrated-storage-compute-deploy-manually)
7. 按需在六台机器上选择几台机器部署 broker，执行`ALTER SYSTEM ADD BROKER broker_name
"fe1:8000","be1:8000",...;`。
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/log-storage-analysis.md
index 5947600c3bd..6982cc6c94a 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/log-storage-analysis.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/log-storage-analysis.md
@@ -51,7 +51,7 @@
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](./install/deploy-manually/integrated-storage-compute-deploy-manually)。
### 第 3 步：优化 FE 和 BE 配置
@@ -82,7 +82,7 @@
| - | `enable_file_cache = true` |
开启文件缓存。 |
| - | `file_cache_path = [{"path": "/mnt/datadisk0/file_cache",
"total_size":53687091200, "query_limit": "10737418240"},{"path":
"/mnt/datadisk1/file_cache", "total_size":53687091200,"query_limit":
"10737418240"}]` | 配置冷数据的缓存路径和相关设置，具体配置说明如下：<br />`path`：缓存路径<br
/>`total_size`：该缓存路径的总大小，单位为字节，53687091200 字节等于 50 GB<br
/>`query_limit`：单次查询可以从缓存路径中查询的最大数据量，单位为字节，10737418240 字节等于 10 GB |
| 写入 | `write_buffer_size = 1073741824` |
增加写入缓冲区（buffer）的文件大小，减少小文件和随机 I/O 操作，提升性能。 |
-| - | `max_tablet_version_num = 20000` |
配合建表的 time_series compaction 策略，允许更多版本暂时未合并。
2.1.11版本后不再需要，有单独的time_series_max_tablet_version_num配置|
+| - | `max_tablet_version_num = 20000` |
配合建表的 time_series compaction 策略，允许更多版本暂时未合并。2.1.11 版本后不再需要，有单独的
time_series_max_tablet_version_num 配置|
| Compaction | `max_cumu_compaction_threads = 8` |
设置为 CPU 核数 / 4，意味着 CPU 资源的 1/4 用于写入，1/4 用于后台 Compaction，2/1 留给查询和其他操作。 |
| - | `inverted_index_compaction_enable = true` |
开启索引合并（index compaction），减少 Compaction 时的 CPU 消耗。 |
| - | `enable_segcompaction = false` `enable_ordered_data_compaction
= false` | 关闭日志场景不需要的两个 Compaction 功能。 |
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log-storage-analysis.md
index 751bfa7fbb7..b76cd34d159 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log-storage-analysis.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log-storage-analysis.md
@@ -51,7 +51,7 @@
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
### 第 3 步：优化 FE 和 BE 配置
@@ -70,7 +70,7 @@
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](../admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -98,7 +98,7 @@
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](../admin-manual/config/be-config)。
### 第 4 步：建表
@@ -107,14 +107,14 @@
**配置分区分桶参数**
分区时，按照以下说明配置：
-- 使用时间字段上的 [Range
分区](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- 使用时间字段上的 [Range
分区](../table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](../table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶时，按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考 [数据划分](../table-design/data-partitioning/data-distribution)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -265,7 +265,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../ecosystem/logstash)。
**对接 Filebeat**
@@ -341,7 +341,7 @@ chmod +x filebeat-doris-1.0.0
./filebeat-doris-1.0.0 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../ecosystem/beats)。
**对接 Kafka**
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log.md
index 6bfd10a07e7..cda1fcc6784 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/version-2.1/observability/log.md
@@ -35,7 +35,7 @@
- BE：15 台服务器，每台配置 32 核 CPU、256 GB 内存、8 块 680 GB SSD 盘
- S3 对象存储空间：即为预估冷数据存储空间，600 TB
-使用存算分离模式，写入和热数据存储只需要 1副本，能够显著降低成本。
+使用存算分离模式，写入和热数据存储只需要 1 副本，能够显著降低成本。
该例子中，各关键指标的值及具体计算方法可见下表：
@@ -61,7 +61,7 @@
## 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
## 第 3 步：优化 FE 和 BE 配置
@@ -80,7 +80,7 @@
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](../admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -108,7 +108,7 @@
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](../admin-manual/config/be-config)。
### 第 4 步：建表
@@ -117,14 +117,14 @@
**配置分区分桶参数**
分区按照以下说明配置：
-- 使用时间字段上的 [Range
分区](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- 使用时间字段上的 [Range
分区](../table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](../table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为排序 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考 [数据划分](../table-design/data-partitioning/data-distribution)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -276,7 +276,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../ecosystem/logstash)。
**对接 Filebeat**
@@ -352,7 +352,7 @@ chmod +x filebeat-doris-7.17.5.4
./filebeat-doris-7.17.5.4 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../ecosystem/beats)。
**对接 Kafka**
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/admin-manual/cluster-management/fqdn.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/admin-manual/cluster-management/fqdn.md
index c0ece8f0877..e190444316c 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/admin-manual/cluster-management/fqdn.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/admin-manual/cluster-management/fqdn.md
@@ -43,7 +43,7 @@ Doris 支持 FQDN 之后，各节点之间通信完全基于 FQDN。添加各类
5. 每个 FE 节点的 fe.conf 设置 `enable_fqdn_mode = true`。
-6.
参考[手动部署](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
+6.
参考[手动部署](../../install/deploy-manually/integrated-storage-compute-deploy-manually)
7. 按需在六台机器上选择几台机器部署 broker，执行`ALTER SYSTEM ADD BROKER broker_name
"fe1:8000","be1:8000",...;`。
@@ -51,7 +51,7 @@ Doris 支持 FQDN 之后，各节点之间通信完全基于 FQDN。添加各类
Pod 意外重启后，K8s 不能保证 Pod 的 IP 不发生变化，但是能保证域名不变，基于这一特性，Doris 开启 FQDN 时，能保证 Pod
意外重启后，还能正常提供服务。
-K8s 部署 Doris 的方法请参考[K8s 部署
Doris](../../../version-3.0/install/deploy-on-kubernetes/integrated-storage-compute/install-doris-cluster)
+K8s 部署 Doris 的方法请参考[K8s 部署
Doris](../../install/deploy-on-kubernetes/integrated-storage-compute/install-doris-cluster)
### 服务器变更 IP
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/log-storage-analysis.md
index 3490ddacb48..c88a5b53074 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/log-storage-analysis.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/log-storage-analysis.md
@@ -51,7 +51,7 @@
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](./install/deploy-manually/integrated-storage-compute-deploy-manually)。
### 第 3 步：优化 FE 和 BE 配置
@@ -82,7 +82,7 @@
| - | `enable_file_cache = true` |
开启文件缓存。 |
| - | `file_cache_path = [{"path": "/mnt/datadisk0/file_cache",
"total_size":53687091200, "query_limit": "10737418240"},{"path":
"/mnt/datadisk1/file_cache", "total_size":53687091200,"query_limit":
"10737418240"}]` | 配置冷数据的缓存路径和相关设置，具体配置说明如下：<br />`path`：缓存路径<br
/>`total_size`：该缓存路径的总大小，单位为字节，53687091200 字节等于 50 GB<br
/>`query_limit`：单次查询可以从缓存路径中查询的最大数据量，单位为字节，10737418240 字节等于 10 GB |
| 写入 | `write_buffer_size = 1073741824` |
增加写入缓冲区（buffer）的文件大小，减少小文件和随机 I/O 操作，提升性能。 |
-| - | `max_tablet_version_num = 20000` |
配合建表的 time_series compaction
策略，允许更多版本暂时未合并。3.0.7版本后不再需要，有单独的time_series_max_tablet_version_num配置 |
+| - | `max_tablet_version_num = 20000` |
配合建表的 time_series compaction 策略，允许更多版本暂时未合并。3.0.7 版本后不再需要，有单独的
time_series_max_tablet_version_num 配置 |
| Compaction | `max_cumu_compaction_threads = 8` |
设置为 CPU 核数 / 4，意味着 CPU 资源的 1/4 用于写入，1/4 用于后台 Compaction，2/1 留给查询和其他操作。 |
| - | `inverted_index_compaction_enable = true` |
开启索引合并（index compaction），减少 Compaction 时的 CPU 消耗。 |
| - | `enable_segcompaction = false` `enable_ordered_data_compaction
= false` | 关闭日志场景不需要的两个 Compaction 功能。 |
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log-storage-analysis.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log-storage-analysis.md
index 751bfa7fbb7..b76cd34d159 100644
---
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log-storage-analysis.md
+++
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log-storage-analysis.md
@@ -51,7 +51,7 @@
### 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
### 第 3 步：优化 FE 和 BE 配置
@@ -70,7 +70,7 @@
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](../admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -98,7 +98,7 @@
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](../admin-manual/config/be-config)。
### 第 4 步：建表
@@ -107,14 +107,14 @@
**配置分区分桶参数**
分区时，按照以下说明配置：
-- 使用时间字段上的 [Range
分区](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- 使用时间字段上的 [Range
分区](../table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](../table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶时，按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考 [数据划分](../table-design/data-partitioning/data-distribution)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -265,7 +265,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../ecosystem/logstash)。
**对接 Filebeat**
@@ -341,7 +341,7 @@ chmod +x filebeat-doris-1.0.0
./filebeat-doris-1.0.0 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../ecosystem/beats)。
**对接 Kafka**
diff --git
a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log.md
b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log.md
index 85e325833d1..9fe0b398ec7 100644
--- a/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log.md
+++ b/i18n/zh-CN/docusaurus-plugin-content-docs/version-3.0/observability/log.md
@@ -35,7 +35,7 @@
- BE：15 台服务器，每台配置 32 核 CPU、256 GB 内存、8 块 680 GB SSD 盘
- S3 对象存储空间：即为预估冷数据存储空间，600 TB
-使用存算分离模式，写入和热数据存储只需要 1副本，能够显著降低成本。
+使用存算分离模式，写入和热数据存储只需要 1 副本，能够显著降低成本。
该例子中，各关键指标的值及具体计算方法可见下表：
@@ -61,7 +61,7 @@
## 第 2 步：部署集群
-完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)。
+完成资源评估后，可以开始部署 Apache Doris 集群，推荐在物理机及虚拟机环境中进行部署。手动部署集群，可参考
[手动部署](../install/deploy-manually/integrated-storage-compute-deploy-manually)。
## 第 3 步：优化 FE 和 BE 配置
@@ -80,7 +80,7 @@
| `autobucket_min_buckets = 10` | 将自动分桶的最小分桶数从
1 调大到 10，避免日志量增加时分桶不够。 |
| `max_backend_heartbeat_failure_tolerance_count = 10` | 日志场景下 BE
服务器压力较大，可能短时间心跳超时，因此将容忍次数从 1 调大到 10。 |
-更多关于 FE 配置项的信息，可参考 [FE 配置项](./admin-manual/config/fe-config)。
+更多关于 FE 配置项的信息，可参考 [FE 配置项](../admin-manual/config/fe-config)。
**优化 BE 配置**
@@ -108,7 +108,7 @@
| 其他 | `string_type_length_soft_limit_bytes = 10485760` | 将
String 类型数据的长度限制调高至 10 MB。 |
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
调快垃圾文件的回收时间。 |
-更多关于 BE 配置项的信息，可参考 [BE 配置项](./admin-manual/config/be-config)。
+更多关于 BE 配置项的信息，可参考 [BE 配置项](../admin-manual/config/be-config)。
### 第 4 步：建表
@@ -117,14 +117,14 @@
**配置分区分桶参数**
分区按照以下说明配置：
-- 使用时间字段上的 [Range
分区](./table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](./table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
+- 使用时间字段上的 [Range
分区](../table-design/data-partitioning/manual-partitioning.md#range-分区)
(`PARTITION BY RANGE(`ts`)`)，并开启
[动态分区](../table-design/data-partitioning/dynamic-partitioning)
(`"dynamic_partition.enable" = "true"`)，按天自动管理分区。
- 使用 Datetime 类型的时间字段作为排序 Key (`DUPLICATE KEY(ts)`)，在查询最新 N 条日志时有数倍加速。
分桶按照以下说明配置：
- 分桶数量大致为集群磁盘总数的 3 倍，每个桶的数据量压缩后 5GB 左右。
- 使用 Random 策略 (`DISTRIBUTED BY RANDOM BUCKETS 60`)，配合写入时的 Single Tablet
导入，可以提升批量（Batch）写入的效率。
-更多关于分区分桶的信息，可参考 [数据划分](./table-design/data-partitioning/data-distribution)。
+更多关于分区分桶的信息，可参考 [数据划分](../table-design/data-partitioning/data-distribution)。
**配置压缩参数**
- 使用 zstd 压缩算法 (`"compression" = "zstd"`), 提高数据压缩率。
@@ -276,7 +276,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](./ecosystem/logstash)。
+更多关于 Logstash 配置和使用的说明，可参考 [Logstash Doris Output
Plugin](../ecosystem/logstash)。
**对接 Filebeat**
@@ -352,7 +352,7 @@ chmod +x filebeat-doris-7.17.5.4
./filebeat-doris-7.17.5.4 -c filebeat_demo.yml
```
-更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](./ecosystem/beats)。
+更多关于 Filebeat 配置和使用的说明，可参考 [Beats Doris Output Plugin](../ecosystem/beats)。
**对接 Kafka**
diff --git a/versioned_docs/version-2.0/ecosystem/beats.md
b/versioned_docs/version-2.0/ecosystem/beats.md
index 0fa5e464e18..1eb1b52a5b3 100644
--- a/versioned_docs/version-2.0/ecosystem/beats.md
+++ b/versioned_docs/version-2.0/ecosystem/beats.md
@@ -11,7 +11,7 @@
The Beats Doris output plugin supports
[Filebeat](https://github.com/elastic/beats/tree/master/filebeat),
[Metricbeat](https://github.com/elastic/beats/tree/master/metricbeat),
[Packetbeat](https://github.com/elastic/beats/tree/master/packetbeat),
[Winlogbeat](https://github.com/elastic/beats/tree/master/winlogbeat),
[Auditbeat](https://github.com/elastic/beats/tree/master/auditbeat), and
[Heartbeat](https://github.com/elastic/beats/tree/master/heartbeat).
-By invoking the [Doris Stream
Load](../data-operate/import/import-way/stream-load-manual) HTTP interface, the
Beats Doris output plugin writes data into Doris in real-time, offering
capabilities such as multi-threaded concurrency, failure retries, custom Stream
Load formats and parameters, and output write speed.
+By invoking the [Doris Stream
Load](../data-operate/import/stream-load-manual.md) HTTP interface, the Beats
Doris output plugin writes data into Doris in real-time, offering capabilities
such as multi-threaded concurrency, failure retries, custom Stream Load formats
and parameters, and output write speed.
To use the Beats Doris output plugin, there are three main steps:
1. Download or compile the Beats binary program that includes the Doris output
plugin.
diff --git a/versioned_docs/version-2.0/ecosystem/fluentbit.md
b/versioned_docs/version-2.0/ecosystem/fluentbit.md
index 9703d44973c..7bc194d6f8d 100644
--- a/versioned_docs/version-2.0/ecosystem/fluentbit.md
+++ b/versioned_docs/version-2.0/ecosystem/fluentbit.md
@@ -7,7 +7,7 @@
[Fluent Bit](https://fluentbit.io/) is a fast log processor and forwarder that
supports custom output plugins to write data into storage systems, with the
Fluent Bit Doris output plugin being the one for outputting to Doris.
-By invoking the [Doris Stream
Load](../data-operate/import/import-way/stream-load-manual) HTTP interface, the
Fluent Bit Doris output plugin writes data into Doris in real-time, offering
capabilities such as multi-threaded concurrency, failure retries, custom Stream
Load formats and parameters, and output write speed.
+By invoking the [Doris Stream
Load](../data-operate/import/stream-load-manual.md) HTTP interface, the Fluent
Bit Doris output plugin writes data into Doris in real-time, offering
capabilities such as multi-threaded concurrency, failure retries, custom Stream
Load formats and parameters, and output write speed.
To use the Fluent Bit Doris output plugin, there are three main steps:
1. Download or compile the Fluent Bit binary program that includes the Doris
output plugin.
diff --git a/versioned_docs/version-2.0/ecosystem/logstash.md
b/versioned_docs/version-2.0/ecosystem/logstash.md
index 81c2689f96f..99ac83937ea 100644
--- a/versioned_docs/version-2.0/ecosystem/logstash.md
+++ b/versioned_docs/version-2.0/ecosystem/logstash.md
@@ -11,7 +11,7 @@
Logstash is a log ETL framework (collect, preprocess, send to storage systems)
that supports custom output plugins to write data into storage systems. The
Logstash Doris output plugin is a plugin for outputting data to Doris.
-The Logstash Doris output plugin calls the [Doris Stream
Load](../data-operate/import/import-way/stream-load-manual) HTTP interface to
write data into Doris in real-time, offering capabilities such as
multi-threaded concurrency, failure retries, custom Stream Load formats and
parameters, and output write speed.
+The Logstash Doris output plugin calls the [Doris Stream
Load](../data-operate/import/stream-load-manual.md) HTTP interface to write
data into Doris in real-time, offering capabilities such as multi-threaded
concurrency, failure retries, custom Stream Load formats and parameters, and
output write speed.
Using the Logstash Doris output plugin mainly involves three steps:
1. Install the plugin into Logstash
diff --git a/versioned_docs/version-2.0/practical-guide/log-storage-analysis.md
b/versioned_docs/version-2.0/practical-guide/log-storage-analysis.md
index 3df8adf56c0..95478900801 100644
--- a/versioned_docs/version-2.0/practical-guide/log-storage-analysis.md
+++ b/versioned_docs/version-2.0/practical-guide/log-storage-analysis.md
@@ -146,7 +146,7 @@ Refer to the following table to learn about the values of
indicators in the exam
### Step 2: Deploy the cluster
-After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../../install/cluster-deployment/standard-deployment.md).
+After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../install/cluster-deployment/standard-deployment.md).
### Step 3: Optimize FE and BE configurations
@@ -165,7 +165,7 @@ You can find FE configuration fields in `fe/conf/fe.conf`.
Refer to the followin
| `autobucket_min_buckets = 10` | Increase the
minimum number of automatically bucketed buckets from 1 to 10 to avoid
insufficient buckets when the log volume increases. |
| `max_backend_heartbeat_failure_tolerance_count = 10` | In log
scenarios, the BE server may experience high pressure, leading to short-term
timeouts, so increase the tolerance count from 1 to 10. |
-For more information, refer to [FE
Configuration](../../admin-manual/config/fe-config.md).
+For more information, refer to [FE
Configuration](../admin-manual/config/fe-config.md).
**Optimize BE configurations**
@@ -194,7 +194,7 @@ You can find BE configuration fields in `be/conf/be.conf`.
Refer to the followin
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
Accelerate the recycling of trash files. |
-For more information, refer to [BE
Configuration](../../admin-manual/config/be-config.md).
+For more information, refer to [BE
Configuration](../admin-manual/config/be-config.md).
### Step 4: Create tables
@@ -204,7 +204,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- For data partitioning:
- - Enable [range
partitioning](../table-design/data-partitioning/manual-partitioning#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](../../table-design/data-partition#dynamic-partition)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
+ - Enable [range
partitioning](../table-design/data-partitioning/manual-partitioning#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](../table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
- Use a field in the DATETIME type as the key (`DUPLICATE KEY(ts)`) for
accelerated retrieval of the latest N log entries.
@@ -214,7 +214,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- Use the Random strategy (`DISTRIBUTED BY RANDOM BUCKETS 60`) to optimize
batch writing efficiency when paired with single tablet imports.
-For more information, refer to [Data
Partitioning](../table-design/data-partitioning/auto-partitioning).
+For more information, refer to [Data
Partitioning](../table-design/data-partitioning/manual-partitioning.md).
**Configure compression parameters**
@@ -367,7 +367,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../../ecosystem/logstash.md).
+For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../ecosystem/logstash.md).
**Integrating Filebeat**
@@ -435,7 +435,7 @@ headers:
./filebeat-doris-1.0.0 -c filebeat_demo.yml
```
-For more information about Filebeat, refer to [Beats Doris Output
Plugin](../../ecosystem/beats.md).
+For more information about Filebeat, refer to [Beats Doris Output
Plugin](../ecosystem/beats.md).
**Integrating Kafka**
diff --git
a/versioned_docs/version-2.1/admin-manual/trouble-shooting/metadata-operation.md
b/versioned_docs/version-2.1/admin-manual/trouble-shooting/metadata-operation.md
index cfc189bad8e..23011468a60 100644
---
a/versioned_docs/version-2.1/admin-manual/trouble-shooting/metadata-operation.md
+++
b/versioned_docs/version-2.1/admin-manual/trouble-shooting/metadata-operation.md
@@ -341,7 +341,7 @@ The third level can display the value information of the
specified key.
## Best Practices
-The deployment recommendation of FE is described in the Installation and
[Deployment
Document](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually).
Here are some supplements.
+The deployment recommendation of FE is described in the Installation and
[Deployment
Document](../../install/deploy-manually/integrated-storage-compute-deploy-manually).
Here are some supplements.
* **If you don't know the operation logic of FE metadata very well, or you
don't have enough experience in the operation and maintenance of FE metadata,
we strongly recommend that only one FOLLOWER-type FE be deployed as MASTER in
practice, and the other FEs are OBSERVER, which can reduce many complex
operation and maintenance problems.** Don't worry too much about the failure of
MASTER single point to write metadata. First, if you configure it properly, FE
as a java process is very diff [...]
diff --git a/versioned_docs/version-2.1/benchmark/ssb.md
b/versioned_docs/version-2.1/benchmark/ssb.md
index 00a7c6e2718..9841f946366 100644
--- a/versioned_docs/version-2.1/benchmark/ssb.md
+++ b/versioned_docs/version-2.1/benchmark/ssb.md
@@ -86,7 +86,7 @@ Here we use Apache Doris 2.0.15.1 for comparative testing. In
the test, we use Q
## 6. Environment Preparation
-Please first refer to the [official
documentation](../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
to install and deploy Apache Doris first to obtain a Doris cluster which is
working well(including at least 1 FE 1 BE, 1 FE 3 BEs is recommended).
+Please first refer to the [official
documentation](../install/deploy-manually/integrated-storage-compute-deploy-manually)
to install and deploy Apache Doris first to obtain a Doris cluster which is
working well(including at least 1 FE 1 BE, 1 FE 3 BEs is recommended).
## 7. Data Preparation
diff --git a/versioned_docs/version-2.1/benchmark/tpcds.md
b/versioned_docs/version-2.1/benchmark/tpcds.md
index b14309e270e..e281f641b9e 100644
--- a/versioned_docs/version-2.1/benchmark/tpcds.md
+++ b/versioned_docs/version-2.1/benchmark/tpcds.md
@@ -181,7 +181,7 @@ The test results are as follows: (Apache Doris 2.0.15.1 q78
q79 failed to execut
## 6. Environmental Preparation
-Please refer to the [official
document](../../version-3.0/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-2.1/benchmark/tpch.md
b/versioned_docs/version-2.1/benchmark/tpch.md
index 3201f5c9d28..e2c71602166 100644
--- a/versioned_docs/version-2.1/benchmark/tpch.md
+++ b/versioned_docs/version-2.1/benchmark/tpch.md
@@ -86,7 +86,7 @@ Here we use Apache Doris 2.1.7-rc03 and Apache Doris 2.0.15.1
for comparative te
## 6. Environmental Preparation
-Please refer to the [official
document](../../version-3.0/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-2.1/log-storage-analysis.md
b/versioned_docs/version-2.1/log-storage-analysis.md
index 21522196892..fa6bb104b33 100644
--- a/versioned_docs/version-2.1/log-storage-analysis.md
+++ b/versioned_docs/version-2.1/log-storage-analysis.md
@@ -156,7 +156,7 @@ Refer to the following table to learn about the values of
indicators in the exam
### Step 2: Deploy the cluster
-After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually).
+After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](./install/deploy-manually/integrated-storage-compute-deploy-manually).
### Step 3: Optimize FE and BE configurations
diff --git a/versioned_docs/version-2.1/observability/log.md
b/versioned_docs/version-2.1/observability/log.md
index 45b32f11027..bac7f33066b 100644
--- a/versioned_docs/version-2.1/observability/log.md
+++ b/versioned_docs/version-2.1/observability/log.md
@@ -70,7 +70,7 @@ Refer to the following table to learn about the values of
indicators in the exam
## Step 2: Deploy the cluster
-After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually).
+After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../install/deploy-manually/integrated-storage-compute-deploy-manually.md).
## Step 3: Optimize FE and BE configurations
@@ -90,7 +90,7 @@ You can find FE configuration fields in `fe/conf/fe.conf`.
Refer to the followin
| `autobucket_min_buckets = 10` | Increase the
minimum number of automatically bucketed buckets from 1 to 10 to avoid
insufficient buckets when the log volume increases. |
| `max_backend_heartbeat_failure_tolerance_count = 10` | In log
scenarios, the BE server may experience high pressure, leading to short-term
timeouts, so increase the tolerance count from 1 to 10. |
-For more information, refer to [FE
Configuration](./admin-manual/config/fe-config.md).
+For more information, refer to [FE
Configuration](../admin-manual/config/fe-config.md).
**Optimize BE configurations**
@@ -119,7 +119,7 @@ You can find BE configuration fields in `be/conf/be.conf`.
Refer to the followin
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
Accelerate the recycling of trash files. |
-For more information, refer to [BE
Configuration](./admin-manual/config/be-config).
+For more information, refer to [BE
Configuration](../admin-manual/config/be-config).
### Step 4: Create tables
@@ -129,7 +129,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- For data partitioning:
- - Enable [range
partitioning](./table-design/data-partitioning/manual-partitioning.md#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](./table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
+ - Enable [range
partitioning](../table-design/data-partitioning/manual-partitioning.md#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](../table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
- Use a field in the DATETIME type as the sort key (`DUPLICATE KEY(ts)`)
for accelerated retrieval of the latest N log entries.
@@ -139,7 +139,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- Use the Random strategy (`DISTRIBUTED BY RANDOM BUCKETS 60`) to optimize
batch writing efficiency when paired with single tablet imports.
-For more information, refer to [Data
Partitioning](./table-design/data-partitioning/auto-partitioning).
+For more information, refer to [Data
Partitioning](../table-design/data-partitioning/auto-partitioning).
**Configure compression parameters**
@@ -294,7 +294,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../../ecosystem/logstash.md).
+For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../ecosystem/logstash.md).
**Integrating Filebeat**
@@ -362,7 +362,7 @@ headers:
./filebeat-doris-7.17.5.4 -c filebeat_demo.yml
```
-For more information about Filebeat, refer to [Beats Doris Output
Plugin](../../ecosystem/beats.md).
+For more information about Filebeat, refer to [Beats Doris Output
Plugin](../ecosystem/beats.md).
**Integrating Kafka**
diff --git a/versioned_docs/version-2.1/practical-guide/log-storage-analysis.md
b/versioned_docs/version-2.1/practical-guide/log-storage-analysis.md
index ee6adf5ca0d..b89294be4cb 100644
--- a/versioned_docs/version-2.1/practical-guide/log-storage-analysis.md
+++ b/versioned_docs/version-2.1/practical-guide/log-storage-analysis.md
@@ -156,7 +156,7 @@ Refer to the following table to learn about the values of
indicators in the exam
### Step 2: Deploy the cluster
-After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually).
+After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../install/deploy-manually/integrated-storage-compute-deploy-manually).
### Step 3: Optimize FE and BE configurations
diff --git
a/versioned_docs/version-2.1/table-design/data-partitioning/common-issues.md
b/versioned_docs/version-2.1/table-design/data-partitioning/common-issues.md
index 249d1307e9f..8d7d3d288f4 100644
--- a/versioned_docs/version-2.1/table-design/data-partitioning/common-issues.md
+++ b/versioned_docs/version-2.1/table-design/data-partitioning/common-issues.md
@@ -20,7 +20,7 @@
- In the fe.log, search for the `Failed to create partition` log entry at
the corresponding timestamp. In this log entry, you may find a series of number
pairs similar to `{10001-10010}`. The first number in the pair represents the
Backend ID, and the second number represents the Tablet ID. For example, this
number pair indicates that the creation of Tablet ID 10010 on Backend ID 10001
failed.
- Go to the be.INFO log of the corresponding Backend and search for Tablet
ID-related logs within the corresponding time period to find error messages.
- Here are some common tablet creation failure errors, including but not
limited to:
- - The BE did not receive the relevant task. In this case, you cannot find
Tablet ID-related logs in be.INFO or the BE reports success but actually fails.
For these issues, please refer to the [Installation and
Deployment](../../../version-3.0/install/deploy-manually/integrated-storage-compute-deploy-manually)
section to check the connectivity between FE and BE.
+ - The BE did not receive the relevant task. In this case, you cannot find
Tablet ID-related logs in be.INFO or the BE reports success but actually fails.
For these issues, please refer to the [Installation and
Deployment](../../install/deploy-manually/integrated-storage-compute-deploy-manually)
section to check the connectivity between FE and BE.
- Pre-allocated memory failure. This may be because the byte length of a
row in the table exceeds 100KB.
- `Too many open files`. The number of open file handles exceeds the
Linux system limit. You need to modify the handle limit of the Linux system.
diff --git a/versioned_docs/version-3.0/observability/log.md
b/versioned_docs/version-3.0/observability/log.md
index 45b32f11027..bac7f33066b 100644
--- a/versioned_docs/version-3.0/observability/log.md
+++ b/versioned_docs/version-3.0/observability/log.md
@@ -70,7 +70,7 @@ Refer to the following table to learn about the values of
indicators in the exam
## Step 2: Deploy the cluster
-After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../versioned_docs/version-2.1/install/deploy-manually/integrated-storage-compute-deploy-manually).
+After estimating the resources, you need to deploy the cluster. It is
recommended to deploy in both physical and virtual environments manually. For
manual deployment, refer to [Manual
Deployment](../install/deploy-manually/integrated-storage-compute-deploy-manually.md).
## Step 3: Optimize FE and BE configurations
@@ -90,7 +90,7 @@ You can find FE configuration fields in `fe/conf/fe.conf`.
Refer to the followin
| `autobucket_min_buckets = 10` | Increase the
minimum number of automatically bucketed buckets from 1 to 10 to avoid
insufficient buckets when the log volume increases. |
| `max_backend_heartbeat_failure_tolerance_count = 10` | In log
scenarios, the BE server may experience high pressure, leading to short-term
timeouts, so increase the tolerance count from 1 to 10. |
-For more information, refer to [FE
Configuration](./admin-manual/config/fe-config.md).
+For more information, refer to [FE
Configuration](../admin-manual/config/fe-config.md).
**Optimize BE configurations**
@@ -119,7 +119,7 @@ You can find BE configuration fields in `be/conf/be.conf`.
Refer to the followin
| - | `trash_file_expire_time_sec = 300`
`path_gc_check_interval_second = 900` `path_scan_interval_second = 900` |
Accelerate the recycling of trash files. |
-For more information, refer to [BE
Configuration](./admin-manual/config/be-config).
+For more information, refer to [BE
Configuration](../admin-manual/config/be-config).
### Step 4: Create tables
@@ -129,7 +129,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- For data partitioning:
- - Enable [range
partitioning](./table-design/data-partitioning/manual-partitioning.md#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](./table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
+ - Enable [range
partitioning](../table-design/data-partitioning/manual-partitioning.md#range-partitioning)
(`PARTITION BY RANGE(`ts`)`) with [dynamic
partitions](../table-design/data-partitioning/dynamic-partitioning.md)
(`"dynamic_partition.enable" = "true"`) managed automatically by day.
- Use a field in the DATETIME type as the sort key (`DUPLICATE KEY(ts)`)
for accelerated retrieval of the latest N log entries.
@@ -139,7 +139,7 @@ Due to the distinct characteristics of both writing and
querying log data, it is
- Use the Random strategy (`DISTRIBUTED BY RANDOM BUCKETS 60`) to optimize
batch writing efficiency when paired with single tablet imports.
-For more information, refer to [Data
Partitioning](./table-design/data-partitioning/auto-partitioning).
+For more information, refer to [Data
Partitioning](../table-design/data-partitioning/auto-partitioning).
**Configure compression parameters**
@@ -294,7 +294,7 @@ output {
./bin/logstash -f logstash_demo.conf
```
-For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../../ecosystem/logstash.md).
+For more information about the Logstash Doris Output plugin, see [Logstash
Doris Output Plugin](../ecosystem/logstash.md).
**Integrating Filebeat**
@@ -362,7 +362,7 @@ headers:
./filebeat-doris-7.17.5.4 -c filebeat_demo.yml
```
-For more information about Filebeat, refer to [Beats Doris Output
Plugin](../../ecosystem/beats.md).
+For more information about Filebeat, refer to [Beats Doris Output
Plugin](../ecosystem/beats.md).
**Integrating Kafka**
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