deploy: f0e4508

getting-started/apache-spark/dataframe-and-dataset.html

@@ -152,7 +152,7 @@ <h3 id="dataframe-and-dataset"><a class="header" href="#dataframe-and-dataset">D
 is where DataFrames originate from. Spark has an optimized SQL query engine that
 can optimize the compute path as well as provide a more efficient representation
 of the rows when given a schema. From the
-<a href="https://spark.apache.org/docs/3.1.2/sql-programming-guide.html#overview">Spark SQL, DataFrames and Datasets
+<a href="https://spark.apache.org/docs/latest/sql-programming-guide.html#overview">Spark SQL, DataFrames and Datasets
 Guide</a>:</p>
 <blockquote>
 <p>Spark SQL is a Spark module for structured data processing. Unlike the basic
@@ -219,7 +219,7 @@ <h3 id="dataframe-and-dataset"><a class="header" href="#dataframe-and-dataset">D
 StructField(numD,DoubleType,false), StructField(numE,LongType,false),
 StructField(numF,DoubleType,false))
 </code></pre>
-<p>An overview of the different <a href="https://spark.apache.org/docs/3.1.2/api/scala/org/apache/spark/sql/types/index.html">Spark SQL types</a>
+<p>An overview of the different <a href="https://spark.apache.org/docs/latest/api/scala/org/apache/spark/sql/types/index.html">Spark SQL types</a>
 can be found online. For the timestamp field we need to specify the format
 according to the <a href="https://docs.oracle.com/javase/8/docs/api/java/text/SimpleDateFormat.html">Javadate format</a>
 —in our case <code>MM/dd/yy:hh:mm</code>. Tying this all together we can build a Dataframe

print.html

@@ -727,7 +727,7 @@ <h3 id="setting-up-spark-in-docker"><a class="header" href="#setting-up-spark-in
 is where DataFrames originate from. Spark has an optimized SQL query engine that
 can optimize the compute path as well as provide a more efficient representation
 of the rows when given a schema. From the
-<a href="https://spark.apache.org/docs/3.1.2/sql-programming-guide.html#overview">Spark SQL, DataFrames and Datasets
+<a href="https://spark.apache.org/docs/latest/sql-programming-guide.html#overview">Spark SQL, DataFrames and Datasets
 Guide</a>:</p>
 <blockquote>
 <p>Spark SQL is a Spark module for structured data processing. Unlike the basic
@@ -794,7 +794,7 @@ <h3 id="setting-up-spark-in-docker"><a class="header" href="#setting-up-spark-in
 StructField(numD,DoubleType,false), StructField(numE,LongType,false),
 StructField(numF,DoubleType,false))
 </code></pre>
-<p>An overview of the different <a href="https://spark.apache.org/docs/3.1.2/api/scala/org/apache/spark/sql/types/index.html">Spark SQL types</a>
+<p>An overview of the different <a href="https://spark.apache.org/docs/latest/api/scala/org/apache/spark/sql/types/index.html">Spark SQL types</a>
 can be found online. For the timestamp field we need to specify the format
 according to the <a href="https://docs.oracle.com/javase/8/docs/api/java/text/SimpleDateFormat.html">Javadate format</a>
 —in our case <code>MM/dd/yy:hh:mm</code>. Tying this all together we can build a Dataframe