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https://issues.apache.org/jira/browse/DRILL-6383?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16464435#comment-16464435
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Paul Rogers commented on DRILL-6383:
------------------------------------
Thanks for the comments. This particular entry is simply about whether it is
useful for Drill to provide misleading type information. A view claims it can
provide types, but it can only if casts are inserted, and cannot provide
accurate cardinality (null, not-null, array) information.
If it is s feature that the information is approximate, then we can simply
document that fact and explain that the types are not useful for understanding
the data returned by the query. (The tool should do a LIMIT 1 query to force
reading actual data and thus to revolve the types for that one query.)
On the other hand, if the goal is to return accurate type information, then the
examples above show that, at present, Drill does not do so.
> View column types, modes are plan-time guesses, not actual types
> ----------------------------------------------------------------
>
> Key: DRILL-6383
> URL: https://issues.apache.org/jira/browse/DRILL-6383
> Project: Apache Drill
> Issue Type: Bug
> Affects Versions: 1.13.0
> Reporter: Paul Rogers
> Priority: Minor
>
> Create a view views and look at the list of columns within the view. You'll
> see that they are often wrong in name, type and mode.
> Consider a very simple CSV file with headers:
> {noformat}
> custId,name,balance,status
> 123,Fred,456.78
> 125,Betty,98.76,VIP
> 128,Barney,1.23,PAST DUE,30
> {noformat}
> Define the simplest possible view:
> {noformat}
> CREATE VIEW myView2 AS SELECT * FROM `csvh/cust.csvh`;
> {noformat}
> Then look at the view file:
> {noformat}
> {
> "name" : "myView2",
> "sql" : "SELECT *\nFROM `csvh/cust.csvh`",
> "fields" : [ {
> "name" : "**",
> "type" : "DYNAMIC_STAR",
> "isNullable" : true
> } ],
> "workspaceSchemaPath" : [ "local", "data" ]
> }
> {noformat}
> It is clear that the view simply captured the plan-time list of the new
> double-star for the wildcard. Since this is not a true type, it should not
> have an `isNullable` attribute.
> OK, we have to spell out the columns:
> {noformat}
> CREATE VIEW myView3 AS SELECT custId FROM `csvh/cust.csvh`;
> {noformat}
> Let's look at the view file:
> {noformat}
> {
> "name" : "myView3",
> "sql" : "SELECT `custId`\nFROM `csvh/cust.csvh`",
> "fields" : [ {
> "name" : "custId",
> "type" : "ANY",
> "isNullable" : true
> } ],
> "workspaceSchemaPath" : [ "local", "data" ]
> }
> {noformat}
> The name is correct. The type is `ANY`, which is wrong. Since this is a CSV
> file, the column type is `VARCHAR`. Further, because this is a CSV file which
> headers, the mode is REQUIRED, but is listed as nullable. To verify:
> {noformat}
> SELECT sqlTypeOf(custId), modeOf(custId) FROM myView3 LIMIT 1;
> +--------------------+-----------+
> | EXPR$0 | EXPR$1 |
> +--------------------+-----------+
> | CHARACTER VARYING | NOT NULL |
> +--------------------+-----------+
> {noformat}
> Now, let's try a CSV file without headers:
> {noformat}
> 123,Fred,456.78
> 125,Betty,98.76,VIP
> {noformat}
> {noformat}
> CREATE VIEW myView4 AS SELECT columns FROM `csv/cust.csv`;
> SELECT * FROM myView4;
> +--------------------------------+
> | columns |
> +--------------------------------+
> | ["123","Fred","456.78"] |
> | ["125","Betty","98.76","VIP"] |
> +--------------------------------+
> {noformat}
> Let's look at the view file:
> {noformat}
> {
> "name" : "myView4",
> "sql" : "SELECT `columns`\nFROM `csv/cust.csv`",
> "fields" : [ {
> "name" : "columns",
> "type" : "ANY",
> "isNullable" : true
> } ],
> "workspaceSchemaPath" : [ "local", "data" ]
> }
> {noformat}
> This is almost non-sensical. `columns` is reported as type `ANY` and
> nullable. But, `columns` is Repeated `VARCHAR` and repeated types cannot be
> nullable.
> The conclusion is that the type information is virtually worthless and the
> `isNullable` information is worse than worthless: it is plain wrong.
> The type information is valid only if the planner can inver types:
> {noformat}
> CREATE VIEW myView5 AS
> SELECT CAST(custId AS INTEGER) AS custId FROM `csvh/cust.csvh`;
> {noformat}
> The view file:
> {noformat}
> {
> "name" : "myView5",
> "sql" : "SELECT CAST(`custId` AS INTEGER) AS `custId`\nFROM
> `csvh/cust.csvh`",
> "fields" : [ {
> "name" : "custId",
> "type" : "INTEGER",
> "isNullable" : true
> } ],
> "workspaceSchemaPath" : [ "local", "data" ]
> }
> {noformat}
> Note that the `type` is inferred from the cast, but `isNullable` is wrong
> because the underlying column is non-nullable:
> {noformat}
> SELECT modeOf(custId) FROM myView5 LIMIT 1;
> +-----------+
> | EXPR$0 |
> +-----------+
> | NOT NULL |
> +-----------+
> {noformat}
> Expected that Drill would run the underlying query as a `LIMIT 0` query to
> extract the actual column types, and use that in the view.
> Or, expected that Drill would simply omit the column list from the view if
> the data is meaningless.
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