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new 286ee8e [doc] fix typo for session (#8610)
286ee8e is described below
commit 286ee8e1d439acfe1a7e5d6c8183cf316af49c5f
Author: GoGoWen <[email protected]>
AuthorDate: Thu Mar 24 09:14:44 2022 +0800
[doc] fix typo for session (#8610)
---
docs/en/administrator-guide/bucket-shuffle-join.md | 2 +-
docs/en/administrator-guide/vectorized-execution-engine.md | 2 +-
docs/zh-CN/administrator-guide/bucket-shuffle-join.md | 2 +-
docs/zh-CN/administrator-guide/vectorized-execution-engine.md | 2 +-
4 files changed, 4 insertions(+), 4 deletions(-)
diff --git a/docs/en/administrator-guide/bucket-shuffle-join.md
b/docs/en/administrator-guide/bucket-shuffle-join.md
index 0e67268..2ac58a2 100644
--- a/docs/en/administrator-guide/bucket-shuffle-join.md
+++ b/docs/en/administrator-guide/bucket-shuffle-join.md
@@ -95,7 +95,7 @@ The join type indicates that the join method to be used
is：`BUCKET_SHUFFLE`。
## Planning rules of Bucket Shuffle Join
-In most scenarios, users only need to turn on the seesion variable by default
to transparently use the performance improvement brought by this join method.
However, if we understand the planning rules of Bucket Shuffle Join, we can use
it to write more efficient SQL.
+In most scenarios, users only need to turn on the session variable by default
to transparently use the performance improvement brought by this join method.
However, if we understand the planning rules of Bucket Shuffle Join, we can use
it to write more efficient SQL.
* Bucket Shuffle Join only works when the join condition is equivalent. The
reason is similar to Colorate Join. They all rely on hash to calculate the
determined data distribution.
* The bucket column of two tables is included in the equivalent join
condition. When the bucket column of the left table is an equivalent join
condition, it has a high probability of being planned as a Bucket Shuffle Join.
diff --git a/docs/en/administrator-guide/vectorized-execution-engine.md
b/docs/en/administrator-guide/vectorized-execution-engine.md
index 425508c..c91d5cc 100644
--- a/docs/en/administrator-guide/vectorized-execution-engine.md
+++ b/docs/en/administrator-guide/vectorized-execution-engine.md
@@ -101,7 +101,7 @@ After the vectorized execution engine is enabled, `V` mark
will be added before
## Some differences from the row-store execution engine
-In most scenarios, users only need to turn on the seesion variable by default
to transparently enable the vectorized execution engine and improve the
performance of SQL execution. However, **the current vectorized execution
engine is different from the original row-stored execution engine in the
following minor details, which requires users to know**. This part of the
difference is divided into two categories
+In most scenarios, users only need to turn on the session variable by default
to transparently enable the vectorized execution engine and improve the
performance of SQL execution. However, **the current vectorized execution
engine is different from the original row-stored execution engine in the
following minor details, which requires users to know**. This part of the
difference is divided into two categories
* **Type A** : functions that need to be deprecated and deprecated or depended
on by the inline execution engine.
* **Type B**: Not supported on the vectorized execution engine in the short
term, but will be supported by development in the future.
diff --git a/docs/zh-CN/administrator-guide/bucket-shuffle-join.md
b/docs/zh-CN/administrator-guide/bucket-shuffle-join.md
index 6f629dd..67ac4a2 100644
--- a/docs/zh-CN/administrator-guide/bucket-shuffle-join.md
+++ b/docs/zh-CN/administrator-guide/bucket-shuffle-join.md
@@ -96,7 +96,7 @@ select * from test join [shuffle] baseall on test.k1 =
baseall.k1;
## Bucket Shuffle Join的规划规则
-在绝大多数场景之中，用户只需要默认打开seesion变量的开关就可以透明的使用这种Join方式带来的性能提升，但是如果了解Bucket Shuffle
Join的规划规则，可以帮助我们利用它写出更加高效的SQL。
+在绝大多数场景之中，用户只需要默认打开session变量的开关就可以透明的使用这种Join方式带来的性能提升，但是如果了解Bucket Shuffle
Join的规划规则，可以帮助我们利用它写出更加高效的SQL。
* Bucket Shuffle Join只生效于Join条件为等值的场景，原因与Colocate Join类似，它们都依赖hash来计算确定的数据分布。
* 在等值Join条件之中包含两张表的分桶列，当左表的分桶列为等值的Join条件时，它有很大概率会被规划为Bucket Shuffle Join。
diff --git a/docs/zh-CN/administrator-guide/vectorized-execution-engine.md
b/docs/zh-CN/administrator-guide/vectorized-execution-engine.md
index b16a12b..acfa4a3 100644
--- a/docs/zh-CN/administrator-guide/vectorized-execution-engine.md
+++ b/docs/zh-CN/administrator-guide/vectorized-execution-engine.md
@@ -100,7 +100,7 @@ set batch_size = 4096;
## 与行存执行引擎的部分差异
-在绝大多数场景之中，用户只需要默认打开seesion变量的开关就可以透明的使向量化执行引擎并且得到SQL执行的性能提升。但是，**目前的向量化执行引擎在下面一些微小的细节上与原先的行存执行引擎存在不同，需要使用者知晓**。这部分区别分为两类
+在绝大多数场景之中，用户只需要默认打开session变量的开关就可以透明的使向量化执行引擎并且得到SQL执行的性能提升。但是，**目前的向量化执行引擎在下面一些微小的细节上与原先的行存执行引擎存在不同，需要使用者知晓**。这部分区别分为两类
* **a类** ：行存执行引擎需要被废弃和不推荐使用或依赖的功能
* **b类**： 短期没有在向量化执行引擎上得到支持，但后续会得到开发支持的功能
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