[MINOR][DOCS] Use proper html tag in markdown

docs/sql-data-sources-hive-tables.md

@@ -88,17 +88,17 @@ creating table, you can create a table using storage handler at Hive side, and u
   <tr>
     <td><code>inputFormat, outputFormat</code></td>
     <td>
-      These 2 options specify the name of a corresponding `InputFormat` and `OutputFormat` class as a string literal,
-      e.g. `org.apache.hadoop.hive.ql.io.orc.OrcInputFormat`. These 2 options must be appeared in a pair, and you can not
-      specify them if you already specified the `fileFormat` option.
+      These 2 options specify the name of a corresponding <code>InputFormat</code> and <code>OutputFormat</code> class as a string literal,
+      e.g. <code>org.apache.hadoop.hive.ql.io.orc.OrcInputFormat</code>. These 2 options must be appeared in a pair, and you can not
+      specify them if you already specified the <code>fileFormat</code> option.
     </td>
   </tr>
 
   <tr>
     <td><code>serde</code></td>
     <td>
-      This option specifies the name of a serde class. When the `fileFormat` option is specified, do not specify this option
-      if the given `fileFormat` already include the information of serde. Currently "sequencefile", "textfile" and "rcfile"
+      This option specifies the name of a serde class. When the <code>fileFormat</code> option is specified, do not specify this option
+      if the given <code>fileFormat</code> already include the information of serde. Currently "sequencefile", "textfile" and "rcfile"
       don't include the serde information and you can use this option with these 3 fileFormats.
     </td>
   </tr>

docs/sql-data-sources-jdbc.md

@@ -60,7 +60,7 @@ the following case-insensitive options:
       The JDBC table that should be read from or written into. Note that when using it in the read
       path anything that is valid in a <code>FROM</code> clause of a SQL query can be used.
       For example, instead of a full table you could also use a subquery in parentheses. It is not
-      allowed to specify `dbtable` and `query` options at the same time.
+      allowed to specify <code>dbtable</code> and <code>query</code> options at the same time.
     </td>
   </tr>
   <tr>
@@ -72,10 +72,10 @@ the following case-insensitive options:
       <code> SELECT &lt;columns&gt; FROM (&lt;user_specified_query&gt;) spark_gen_alias</code><br><br>
       Below are a couple of restrictions while using this option.<br>
       <ol>
-         <li> It is not allowed to specify `dbtable` and `query` options at the same time. </li>
-         <li> It is not allowed to specify `query` and `partitionColumn` options at the same time. When specifying
-            `partitionColumn` option is required, the subquery can be specified using `dbtable` option instead and
-            partition columns can be qualified using the subquery alias provided as part of `dbtable`. <br>
+         <li> It is not allowed to specify <code>dbtable</code> and <code>query</code> options at the same time. </li>
+         <li> It is not allowed to specify <code>query</code> and <code>partitionColumn</code> options at the same time. When specifying
+            <code>partitionColumn</code> option is required, the subquery can be specified using <code>dbtable</code> option instead and
+            partition columns can be qualified using the subquery alias provided as part of <code>dbtable</code>. <br>
             Example:<br>
             <code>
                spark.read.format("jdbc")<br>

docs/sql-data-sources-parquet.md

@@ -280,12 +280,12 @@ Configuration of Parquet can be done using the `setConf` method on `SparkSession
   <td><code>spark.sql.parquet.compression.codec</code></td>
   <td>snappy</td>
   <td>
-    Sets the compression codec used when writing Parquet files. If either `compression` or
-    `parquet.compression` is specified in the table-specific options/properties, the precedence would be
-    `compression`, `parquet.compression`, `spark.sql.parquet.compression.codec`. Acceptable values include:
+    Sets the compression codec used when writing Parquet files. If either <code>compression</code> or
+    <code>parquet.compression</code> is specified in the table-specific options/properties, the precedence would be
+    <code>compression</code>, <code>parquet.compression</code>, <code>spark.sql.parquet.compression.codec</code>. Acceptable values include:
     none, uncompressed, snappy, gzip, lzo, brotli, lz4, zstd.
-    Note that `zstd` requires `ZStandardCodec` to be installed before Hadoop 2.9.0, `brotli` requires
-    `BrotliCodec` to be installed.
+    Note that <code>zstd</code> requires <code>ZStandardCodec</code> to be installed before Hadoop 2.9.0, <code>brotli</code> requires
+    <code>BrotliCodec</code> to be installed.
   </td>
 </tr>
 <tr>

docs/structured-streaming-kafka-integration.md

@@ -473,16 +473,16 @@ The following configurations are optional:
   <td>Desired minimum number of partitions to read from Kafka.
   By default, Spark has a 1-1 mapping of topicPartitions to Spark partitions consuming from Kafka.
   If you set this option to a value greater than your topicPartitions, Spark will divvy up large
-  Kafka partitions to smaller pieces. Please note that this configuration is like a `hint`: the
-  number of Spark tasks will be **approximately** `minPartitions`. It can be less or more depending on
+  Kafka partitions to smaller pieces. Please note that this configuration is like a <code>hint</code>: the
+  number of Spark tasks will be <strong>approximately</strong> <code>minPartitions</code>. It can be less or more depending on
   rounding errors or Kafka partitions that didn't receive any new data.</td>
 </tr>
 <tr>
   <td>groupIdPrefix</td>
   <td>string</td>
   <td>spark-kafka-source</td>
   <td>streaming and batch</td>
-  <td>Prefix of consumer group identifiers (`group.id`) that are generated by structured streaming
+  <td>Prefix of consumer group identifiers (<code>group.id</code>) that are generated by structured streaming
   queries. If "kafka.group.id" is set, this option will be ignored.</td>
 </tr>
 <tr>

docs/structured-streaming-programming-guide.md

@@ -1717,7 +1717,7 @@ Here is the compatibility matrix.
     <td style="vertical-align: middle;">Append, Update, Complete</td>
     <td>
         Append mode uses watermark to drop old aggregation state. But the output of a 
-        windowed aggregation is delayed the late threshold specified in `withWatermark()` as by
+        windowed aggregation is delayed the late threshold specified in <code>withWatermark()</code> as by
         the modes semantics, rows can be added to the Result Table only once after they are 
         finalized (i.e. after watermark is crossed). See the
         <a href="#handling-late-data-and-watermarking">Late Data</a> section for more details.
@@ -2324,7 +2324,7 @@ Here are the different kinds of triggers that are supported.
   <tr>
     <td><b>One-time micro-batch</b></td>
     <td>
-        The query will execute *only one* micro-batch to process all the available data and then
+        The query will execute <strong>only one</strong> micro-batch to process all the available data and then
         stop on its own. This is useful in scenarios you want to periodically spin up a cluster,
         process everything that is available since the last period, and then shutdown the
         cluster. In some case, this may lead to significant cost savings.