dilipbiswal commented on a change in pull request #28433:
URL: https://github.com/apache/spark/pull/28433#discussion_r419015360
##########
File path: docs/sql-ref-ansi-compliance.md
##########
@@ -27,35 +27,10 @@ The casting behaviours are defined as store assignment
rules in the standard.
When `spark.sql.storeAssignmentPolicy` is set to `ANSI`, Spark SQL complies
with the ANSI store assignment rules. This is a separate configuration because
its default value is `ANSI`, while the configuration `spark.sql.ansi.enabled`
is disabled by default.
-<table class="table">
-<tr><th>Property Name</th><th>Default</th><th>Meaning</th><th>Since
Version</th></tr>
-<tr>
- <td><code>spark.sql.ansi.enabled</code></td>
- <td>false</td>
- <td>
- (Experimental) When true, Spark tries to conform to the ANSI SQL
specification:
- 1. Spark will throw a runtime exception if an overflow occurs in any
operation on integral/decimal field.
- 2. Spark will forbid using the reserved keywords of ANSI SQL as
identifiers in the SQL parser.
- </td>
- <td>3.0.0</td>
-</tr>
-<tr>
- <td><code>spark.sql.storeAssignmentPolicy</code></td>
- <td>ANSI</td>
- <td>
- (Experimental) When inserting a value into a column with different data
type, Spark will perform type coercion.
- Currently, we support 3 policies for the type coercion rules: ANSI, legacy
and strict. With ANSI policy,
- Spark performs the type coercion as per ANSI SQL. In practice, the
behavior is mostly the same as PostgreSQL.
- It disallows certain unreasonable type conversions such as converting
string to int or double to boolean.
- With legacy policy, Spark allows the type coercion as long as it is a
valid Cast, which is very loose.
- e.g. converting string to int or double to boolean is allowed.
- It is also the only behavior in Spark 2.x and it is compatible with Hive.
- With strict policy, Spark doesn't allow any possible precision loss or
data truncation in type coercion,
- e.g. converting double to int or decimal to double is not allowed.
- </td>
- <td>3.0.0</td>
-</tr>
-</table>
+|Property Name|Default|Meaning|Since Version|
+|-------------|-------|-------|-------------|
+|`spark.sql.ansi.enabled`|false|(Experimental) When true, Spark tries to
conform to the ANSI SQL specification: <br> 1. Spark will throw a runtime
exception if an overflow occurs in any operation on integral/decimal field.
<br> 2. Spark will forbid using the reserved keywords of ANSI SQL as
identifiers in the SQL parser.|3.0.0|
Review comment:
@srowen Replaced <br> with <br/> for all the files in this PR. Will look
at other files and follow-up if needed. About the wrapping in markdown, i
couldn't find any markup syntax to control the cell width. I tried specifying a
style for table in the doc and that seems to work ok.
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