Replace '++version++' to the respective version for released versions

Signed-off-by: Martin Tzvetanov Grigorov <[email protected]>
apache · Aug 26, 2024 · 221057d · 221057d
1 parent c69bf6e
commit 221057d
Show file tree

Hide file tree

Showing 12 changed files with 52 additions and 52 deletions.
diff --git a/doc/content/en/docs/1.11.1/Getting started (Java)/_index.md b/doc/content/en/docs/1.11.1/Getting started (Java)/_index.md
@@ -31,15 +31,15 @@ This is a short guide for getting started with Apache Avro™ using Java. This g
 
 ## Download
 
-Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the [Apache Avro™ Download]({{< relref "/project/download" >}}) page. This guide uses Avro {{< avro_version >}}, the latest version at the time of writing. For the examples in this guide, download avro-{{< avro_version >}}.jar and avro-tools-{{< avro_version >}}.jar.
+Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the [Apache Avro™ Download]({{< relref "/project/download" >}}) page. This guide uses Avro 1.11.1, the latest version at the time of writing. For the examples in this guide, download avro-1.11.1.jar and avro-tools-1.11.1.jar.
 
 Alternatively, if you are using Maven, add the following dependency to your POM:
 
 ```xml
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.1</version>
 </dependency>
 ```
 
@@ -49,7 +49,7 @@ As well as the Avro Maven plugin (for performing code generation):
 <plugin>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-maven-plugin</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.1</version>
   <executions>
     <execution>
       <phase>generate-sources</phase>
@@ -101,13 +101,13 @@ Fields are defined via an array of objects, each of which defines a name and typ
 Code generation allows us to automatically create classes based on our previously-defined schema. Once we have defined the relevant classes, there is no need to use the schema directly in our programs. We use the avro-tools jar to generate code as follows:
 
 ```shell
-java -jar /path/to/avro-tools-{{< avro_version >}}.jar compile schema <schema file> <destination>
+java -jar /path/to/avro-tools-1.11.1.jar compile schema <schema file> <destination>
 ```
 
 This will generate the appropriate source files in a package based on the schema's namespace in the provided destination folder. For instance, to generate a User class in package example.avro from the schema defined above, run
 
 ```shell
-java -jar /path/to/avro-tools-{{< avro_version >}}.jar compile schema user.avsc .
+java -jar /path/to/avro-tools-1.11.1.jar compile schema user.avsc .
 ```
 
 Note that if you using the Avro Maven plugin, there is no need to manually invoke the schema compiler; the plugin automatically performs code generation on any .avsc files present in the configured source directory.

diff --git a/doc/content/en/docs/1.11.1/Getting started (Python)/_index.md b/doc/content/en/docs/1.11.1/Getting started (Python)/_index.md
@@ -39,11 +39,11 @@ For Python, the easiest way to get started is to install it from PyPI. Python's
 $ python3 -m pip install avro
 ```
 
-The official releases of the Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the Apache Avro™ Releases page. This guide uses Avro {{< avro_version >}}, the latest version at the time of writing. Download and unzip avro-{{< avro_version >}}.tar.gz, and install via python setup.py (this will probably require root privileges). Ensure that you can import avro from a Python prompt.
+The official releases of the Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the Apache Avro™ Releases page. This guide uses Avro 1.11.1, the latest version at the time of writing. Download and unzip avro-1.11.1.tar.gz, and install via python setup.py (this will probably require root privileges). Ensure that you can import avro from a Python prompt.
 
 ```shell
-$ tar xvf avro-{{< avro_version >}}.tar.gz
-$ cd avro-{{< avro_version >}}
+$ tar xvf avro-1.11.1.tar.gz
+$ cd avro-1.11.1
 $ python setup.py install
 $ python
 >>> import avro # should not raise ImportError

diff --git a/doc/content/en/docs/1.11.1/MapReduce guide/_index.md b/doc/content/en/docs/1.11.1/MapReduce guide/_index.md
@@ -35,12 +35,12 @@ The code from this guide is included in the Avro docs under examples/mr-example.
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.1</version>
 </dependency>
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-mapred</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.1</version>
 </dependency>
 <dependency>
   <groupId>org.apache.hadoop</groupId>
@@ -53,7 +53,7 @@ And the following plugin:
 <plugin>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-maven-plugin</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.1</version>
   <executions>
     <execution>
       <phase>generate-sources</phase>
@@ -71,7 +71,7 @@ And the following plugin:
 
 If you do not configure the *sourceDirectory* and *outputDirectory* properties, the defaults will be used. The *sourceDirectory* property defaults to *src/main/avro*. The *outputDirectory* property defaults to *target/generated-sources*. You can change the paths to match your project layout.
 
-Alternatively, Avro jars can be downloaded directly from the Apache Avro™ Releases [page](https://avro.apache.org/releases.html). The relevant Avro jars for this guide are *avro-{{< avro_version >}}.jar* and *avro-mapred-{{< avro_version >}}.jar*, as well as *avro-tools-{{< avro_version >}}.jar* for code generation and viewing Avro data files as JSON. In addition, you will need to install Hadoop in order to use MapReduce.
+Alternatively, Avro jars can be downloaded directly from the Apache Avro™ Releases [page](https://avro.apache.org/releases.html). The relevant Avro jars for this guide are *avro-1.11.1.jar* and *avro-mapred-1.11.1.jar*, as well as *avro-tools-1.11.1.jar* for code generation and viewing Avro data files as JSON. In addition, you will need to install Hadoop in order to use MapReduce.
 
 ## Example: ColorCount
 Below is a simple example of a MapReduce that uses Avro. There is an example for both the old (org.apache.hadoop.mapred) and new (org.apache.hadoop.mapreduce) APIs under *examples/mr-example/src/main/java/example/*. _MapredColorCount_ is the example for the older mapred API while _MapReduceColorCount_ is the example for the newer mapreduce API. Both examples are below, but we will detail the mapred API in our subsequent examples.
@@ -291,7 +291,7 @@ part-00000.avro  _SUCCESS
 ```
 You can check the contents of the generated Avro file using the avro-tools jar:
 ```shell
-$ java -jar /path/to/avro-tools-{{< avro_version >}}.jar tojson output/part-00000.avro
+$ java -jar /path/to/avro-tools-1.11.1.jar tojson output/part-00000.avro
 {"value": 3, "key": "blue"}
 {"value": 7, "key": "green"}
 {"value": 1, "key": "none"}

diff --git a/doc/content/en/docs/1.11.2/Getting started (Java)/_index.md b/doc/content/en/docs/1.11.2/Getting started (Java)/_index.md
@@ -31,15 +31,15 @@ This is a short guide for getting started with Apache Avro™ using Java. This g
 
 ## Download
 
-Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the [Apache Avro™ Download]({{< relref "/project/download" >}}) page. This guide uses Avro {{< avro_version >}}, the latest version at the time of writing. For the examples in this guide, download avro-{{< avro_version >}}.jar and avro-tools-{{< avro_version >}}.jar.
+Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the [Apache Avro™ Download]({{< relref "/project/download" >}}) page. This guide uses Avro 1.11.2, the latest version at the time of writing. For the examples in this guide, download avro-1.11.2.jar and avro-tools-1.11.2.jar.
 
 Alternatively, if you are using Maven, add the following dependency to your POM:
 
 ```xml
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.2</version>
 </dependency>
 ```
 
@@ -49,7 +49,7 @@ As well as the Avro Maven plugin (for performing code generation):
 <plugin>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-maven-plugin</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.2</version>
   <executions>
     <execution>
       <phase>generate-sources</phase>
@@ -101,13 +101,13 @@ Fields are defined via an array of objects, each of which defines a name and typ
 Code generation allows us to automatically create classes based on our previously-defined schema. Once we have defined the relevant classes, there is no need to use the schema directly in our programs. We use the avro-tools jar to generate code as follows:
 
 ```shell
-java -jar /path/to/avro-tools-{{< avro_version >}}.jar compile schema <schema file> <destination>
+java -jar /path/to/avro-tools-1.11.2.jar compile schema <schema file> <destination>
 ```
 
 This will generate the appropriate source files in a package based on the schema's namespace in the provided destination folder. For instance, to generate a User class in package example.avro from the schema defined above, run
 
 ```shell
-java -jar /path/to/avro-tools-{{< avro_version >}}.jar compile schema user.avsc .
+java -jar /path/to/avro-tools-1.11.2.jar compile schema user.avsc .
 ```
 
 Note that if you using the Avro Maven plugin, there is no need to manually invoke the schema compiler; the plugin automatically performs code generation on any .avsc files present in the configured source directory.

diff --git a/doc/content/en/docs/1.11.2/Getting started (Python)/_index.md b/doc/content/en/docs/1.11.2/Getting started (Python)/_index.md
@@ -39,11 +39,11 @@ For Python, the easiest way to get started is to install it from PyPI. Python's
 $ python3 -m pip install avro
 ```
 
-The official releases of the Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the Apache Avro™ Releases page. This guide uses Avro {{< avro_version >}}, the latest version at the time of writing. Download and unzip avro-{{< avro_version >}}.tar.gz, and install via python setup.py (this will probably require root privileges). Ensure that you can import avro from a Python prompt.
+The official releases of the Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the Apache Avro™ Releases page. This guide uses Avro 1.11.2, the latest version at the time of writing. Download and unzip avro-1.11.2.tar.gz, and install via python setup.py (this will probably require root privileges). Ensure that you can import avro from a Python prompt.
 
 ```shell
-$ tar xvf avro-{{< avro_version >}}.tar.gz
-$ cd avro-{{< avro_version >}}
+$ tar xvf avro-1.11.2.tar.gz
+$ cd avro-1.11.2
 $ python setup.py install
 $ python
 >>> import avro # should not raise ImportError

diff --git a/doc/content/en/docs/1.11.2/MapReduce guide/_index.md b/doc/content/en/docs/1.11.2/MapReduce guide/_index.md
@@ -35,12 +35,12 @@ The code from this guide is included in the Avro docs under examples/mr-example.
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.2</version>
 </dependency>
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-mapred</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.2</version>
 </dependency>
 <dependency>
   <groupId>org.apache.hadoop</groupId>
@@ -53,7 +53,7 @@ And the following plugin:
 <plugin>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-maven-plugin</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.2</version>
   <executions>
     <execution>
       <phase>generate-sources</phase>
@@ -71,7 +71,7 @@ And the following plugin:
 
 If you do not configure the *sourceDirectory* and *outputDirectory* properties, the defaults will be used. The *sourceDirectory* property defaults to *src/main/avro*. The *outputDirectory* property defaults to *target/generated-sources*. You can change the paths to match your project layout.
 
-Alternatively, Avro jars can be downloaded directly from the Apache Avro™ Releases [page](https://avro.apache.org/releases.html). The relevant Avro jars for this guide are *avro-{{< avro_version >}}.jar* and *avro-mapred-{{< avro_version >}}.jar*, as well as *avro-tools-{{< avro_version >}}.jar* for code generation and viewing Avro data files as JSON. In addition, you will need to install Hadoop in order to use MapReduce.
+Alternatively, Avro jars can be downloaded directly from the Apache Avro™ Releases [page](https://avro.apache.org/releases.html). The relevant Avro jars for this guide are *avro-1.11.2.jar* and *avro-mapred-1.11.2.jar*, as well as *avro-tools-1.11.2.jar* for code generation and viewing Avro data files as JSON. In addition, you will need to install Hadoop in order to use MapReduce.
 
 ## Example: ColorCount
 Below is a simple example of a MapReduce that uses Avro. There is an example for both the old (org.apache.hadoop.mapred) and new (org.apache.hadoop.mapreduce) APIs under *examples/mr-example/src/main/java/example/*. _MapredColorCount_ is the example for the older mapred API while _MapReduceColorCount_ is the example for the newer mapreduce API. Both examples are below, but we will detail the mapred API in our subsequent examples.
@@ -291,7 +291,7 @@ part-00000.avro  _SUCCESS
 ```
 You can check the contents of the generated Avro file using the avro-tools jar:
 ```shell
-$ java -jar /path/to/avro-tools-{{< avro_version >}}.jar tojson output/part-00000.avro
+$ java -jar /path/to/avro-tools-1.11.2.jar tojson output/part-00000.avro
 {"value": 3, "key": "blue"}
 {"value": 7, "key": "green"}
 {"value": 1, "key": "none"}

diff --git a/doc/content/en/docs/1.11.3/Getting started (Java)/_index.md b/doc/content/en/docs/1.11.3/Getting started (Java)/_index.md
@@ -31,15 +31,15 @@ This is a short guide for getting started with Apache Avro™ using Java. This g
 
 ## Download
 
-Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the [Apache Avro™ Download]({{< relref "/project/download" >}}) page. This guide uses Avro {{< avro_version >}}, the latest version at the time of writing. For the examples in this guide, download avro-{{< avro_version >}}.jar and avro-tools-{{< avro_version >}}.jar.
+Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the [Apache Avro™ Download]({{< relref "/project/download" >}}) page. This guide uses Avro 1.11.3, the latest version at the time of writing. For the examples in this guide, download avro-1.11.3.jar and avro-tools-1.11.3.jar.
 
 Alternatively, if you are using Maven, add the following dependency to your POM:
 
 ```xml
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.3</version>
 </dependency>
 ```
 
@@ -49,7 +49,7 @@ As well as the Avro Maven plugin (for performing code generation):
 <plugin>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-maven-plugin</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.3</version>
   <executions>
     <execution>
       <phase>generate-sources</phase>
@@ -101,13 +101,13 @@ Fields are defined via an array of objects, each of which defines a name and typ
 Code generation allows us to automatically create classes based on our previously-defined schema. Once we have defined the relevant classes, there is no need to use the schema directly in our programs. We use the avro-tools jar to generate code as follows:
 
 ```shell
-java -jar /path/to/avro-tools-{{< avro_version >}}.jar compile schema <schema file> <destination>
+java -jar /path/to/avro-tools-1.11.3.jar compile schema <schema file> <destination>
 ```
 
 This will generate the appropriate source files in a package based on the schema's namespace in the provided destination folder. For instance, to generate a User class in package example.avro from the schema defined above, run
 
 ```shell
-java -jar /path/to/avro-tools-{{< avro_version >}}.jar compile schema user.avsc .
+java -jar /path/to/avro-tools-1.11.3.jar compile schema user.avsc .
 ```
 
 Note that if you using the Avro Maven plugin, there is no need to manually invoke the schema compiler; the plugin automatically performs code generation on any .avsc files present in the configured source directory.

diff --git a/doc/content/en/docs/1.11.3/Getting started (Python)/_index.md b/doc/content/en/docs/1.11.3/Getting started (Python)/_index.md
@@ -39,11 +39,11 @@ For Python, the easiest way to get started is to install it from PyPI. Python's
 $ python3 -m pip install avro
 ```
 
-The official releases of the Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the Apache Avro™ Releases page. This guide uses Avro {{< avro_version >}}, the latest version at the time of writing. Download and unzip avro-{{< avro_version >}}.tar.gz, and install via python setup.py (this will probably require root privileges). Ensure that you can import avro from a Python prompt.
+The official releases of the Avro implementations for C, C++, C#, Java, PHP, Python, and Ruby can be downloaded from the Apache Avro™ Releases page. This guide uses Avro 1.11.3, the latest version at the time of writing. Download and unzip avro-1.11.3.tar.gz, and install via python setup.py (this will probably require root privileges). Ensure that you can import avro from a Python prompt.
 
 ```shell
-$ tar xvf avro-{{< avro_version >}}.tar.gz
-$ cd avro-{{< avro_version >}}
+$ tar xvf avro-1.11.3.tar.gz
+$ cd avro-1.11.3
 $ python setup.py install
 $ python
 >>> import avro # should not raise ImportError

diff --git a/doc/content/en/docs/1.11.3/MapReduce guide/_index.md b/doc/content/en/docs/1.11.3/MapReduce guide/_index.md
@@ -35,12 +35,12 @@ The code from this guide is included in the Avro docs under examples/mr-example.
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.3</version>
 </dependency>
 <dependency>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-mapred</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.3</version>
 </dependency>
 <dependency>
   <groupId>org.apache.hadoop</groupId>
@@ -53,7 +53,7 @@ And the following plugin:
 <plugin>
   <groupId>org.apache.avro</groupId>
   <artifactId>avro-maven-plugin</artifactId>
-  <version>{{< avro_version >}}</version>
+  <version>1.11.3</version>
   <executions>
     <execution>
       <phase>generate-sources</phase>
@@ -71,7 +71,7 @@ And the following plugin:
 
 If you do not configure the *sourceDirectory* and *outputDirectory* properties, the defaults will be used. The *sourceDirectory* property defaults to *src/main/avro*. The *outputDirectory* property defaults to *target/generated-sources*. You can change the paths to match your project layout.
 
-Alternatively, Avro jars can be downloaded directly from the Apache Avro™ Releases [page](https://avro.apache.org/releases.html). The relevant Avro jars for this guide are *avro-{{< avro_version >}}.jar* and *avro-mapred-{{< avro_version >}}.jar*, as well as *avro-tools-{{< avro_version >}}.jar* for code generation and viewing Avro data files as JSON. In addition, you will need to install Hadoop in order to use MapReduce.
+Alternatively, Avro jars can be downloaded directly from the Apache Avro™ Releases [page](https://avro.apache.org/releases.html). The relevant Avro jars for this guide are *avro-1.11.3.jar* and *avro-mapred-1.11.3.jar*, as well as *avro-tools-1.11.3.jar* for code generation and viewing Avro data files as JSON. In addition, you will need to install Hadoop in order to use MapReduce.
 
 ## Example: ColorCount
 Below is a simple example of a MapReduce that uses Avro. There is an example for both the old (org.apache.hadoop.mapred) and new (org.apache.hadoop.mapreduce) APIs under *examples/mr-example/src/main/java/example/*. _MapredColorCount_ is the example for the older mapred API while _MapReduceColorCount_ is the example for the newer mapreduce API. Both examples are below, but we will detail the mapred API in our subsequent examples.
@@ -291,7 +291,7 @@ part-00000.avro  _SUCCESS
 ```
 You can check the contents of the generated Avro file using the avro-tools jar:
 ```shell
-$ java -jar /path/to/avro-tools-{{< avro_version >}}.jar tojson output/part-00000.avro
+$ java -jar /path/to/avro-tools-1.11.3.jar tojson output/part-00000.avro
 {"value": 3, "key": "blue"}
 {"value": 7, "key": "green"}
 {"value": 1, "key": "none"}