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The following commit(s) were added to refs/heads/dev by this push:
new d0ea75ce7a fix the typos[mutiple -> multiple] in introduction.md (#597)
d0ea75ce7a is described below
commit d0ea75ce7ab6f8c52843d278a86fc7b99c911196
Author: GuoPhilipse <[email protected]>
AuthorDate: Mon Nov 21 11:32:54 2022 +0800
fix the typos[mutiple -> multiple] in introduction.md (#597)
---
docs/introduction.md | 2 +-
versioned_docs/version-1.0.2/introduction.md | 2 +-
versioned_docs/version-1.0.3/introduction.md | 2 +-
versioned_docs/version-1.1.0/introduction.md | 2 +-
versioned_docs/version-1.1.1/introduction.md | 2 +-
versioned_docs/version-1.1.2/introduction.md | 2 +-
versioned_docs/version-1.1.3/introduction.md | 2 +-
versioned_docs/version-1.2.0/introduction.md | 2 +-
versioned_docs/version-1.3.0/introduction.md | 2 +-
9 files changed, 9 insertions(+), 9 deletions(-)
diff --git a/docs/introduction.md b/docs/introduction.md
index d5ec42677c..70d345eafe 100644
--- a/docs/introduction.md
+++ b/docs/introduction.md
@@ -22,7 +22,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
diff --git a/versioned_docs/version-1.0.2/introduction.md
b/versioned_docs/version-1.0.2/introduction.md
index 0df12d3dd1..e39b86321f 100644
--- a/versioned_docs/version-1.0.2/introduction.md
+++ b/versioned_docs/version-1.0.2/introduction.md
@@ -26,7 +26,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each task/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
diff --git a/versioned_docs/version-1.0.3/introduction.md
b/versioned_docs/version-1.0.3/introduction.md
index 2eceb54bba..d5119717e1 100644
--- a/versioned_docs/version-1.0.3/introduction.md
+++ b/versioned_docs/version-1.0.3/introduction.md
@@ -26,7 +26,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each task/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
diff --git a/versioned_docs/version-1.1.0/introduction.md
b/versioned_docs/version-1.1.0/introduction.md
index a43bf55be6..64e02dd453 100644
--- a/versioned_docs/version-1.1.0/introduction.md
+++ b/versioned_docs/version-1.1.0/introduction.md
@@ -23,7 +23,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
diff --git a/versioned_docs/version-1.1.1/introduction.md
b/versioned_docs/version-1.1.1/introduction.md
index a43bf55be6..64e02dd453 100644
--- a/versioned_docs/version-1.1.1/introduction.md
+++ b/versioned_docs/version-1.1.1/introduction.md
@@ -23,7 +23,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
diff --git a/versioned_docs/version-1.1.2/introduction.md
b/versioned_docs/version-1.1.2/introduction.md
index a43bf55be6..64e02dd453 100644
--- a/versioned_docs/version-1.1.2/introduction.md
+++ b/versioned_docs/version-1.1.2/introduction.md
@@ -23,7 +23,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
diff --git a/versioned_docs/version-1.1.3/introduction.md
b/versioned_docs/version-1.1.3/introduction.md
index a43bf55be6..64e02dd453 100644
--- a/versioned_docs/version-1.1.3/introduction.md
+++ b/versioned_docs/version-1.1.3/introduction.md
@@ -23,7 +23,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
diff --git a/versioned_docs/version-1.2.0/introduction.md
b/versioned_docs/version-1.2.0/introduction.md
index a43bf55be6..64e02dd453 100644
--- a/versioned_docs/version-1.2.0/introduction.md
+++ b/versioned_docs/version-1.2.0/introduction.md
@@ -23,7 +23,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
diff --git a/versioned_docs/version-1.3.0/introduction.md
b/versioned_docs/version-1.3.0/introduction.md
index d5ec42677c..70d345eafe 100644
--- a/versioned_docs/version-1.3.0/introduction.md
+++ b/versioned_docs/version-1.3.0/introduction.md
@@ -22,7 +22,7 @@ Since the first release of Linkis in 2019, it has accumulated
more than **700**
Supported scripting languages: SparkSQL, HiveQL, Python, Shell, Pyspark,
R, Scala and JDBC, etc.
- **Powerful task/request governance capabilities**. With services such as
Orchestrator, Label Manager and customized Spring Cloud Gateway, Linkis is able
to provide multi-level labels based, cross-cluster/cross-IDC fine-grained
routing, load balance, multi-tenancy, traffic control, resource control, and
orchestration strategies like dual-active, active-standby, etc.
- **Support full stack computation/storage engine**. As a computation
middleware, it will receive, execute and manage tasks and requests for various
computation storage engines, including batch tasks, interactive query tasks,
real-time streaming tasks and storage tasks;
-- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
mutiple Yarn clusters and mutiple computation resource types;
+- **Resource management capabilities**. ResourceManager is not only capable
of managing resources for Yarn and Linkis EngineManger as in Linkis 0.X, but
also able to provide label-based multi-level resource allocation and recycling,
allowing itself to have powerful resource management capabilities across
multiple Yarn clusters and multiple computation resource types;
- **Unified Context Service**. Generate Context ID for each **task**/request,
associate and manage user and system resource files (JAR, ZIP, Properties,
etc.), result set, parameter variable, function, etc., across user, system, and
computing engine. Set in one place, automatic reference everywhere;
- **Unified materials**. System and user-level unified material management,
which can be shared and transferred across users and systems.
- **Unified Data Source Manage**. Provides functions such as adding, deleting,
checking, and modifying data sources of hive, es, mysql, and kafka types,
version control, and connection testing.
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