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= Use Cases =

Views are a standard DBMS feature and their uses are well understood.  A 
typical use case might be to create an interface layer with a consistent 
entity/attribute naming scheme on top of an existing set of inconsistently 
named tables, without having to cause disruption due to direct modification of 
the tables.  More advanced use cases would involve predefined filters, joins, 
aggregations, etc for simplifying query construction by end users, as well as 
sharing common definitions within ETL pipelines.

= Scope =

At a minimum, we want to 

* add queryable view support at the SQL language level (specifics of the 
scoping are under discussion in the Issues section below)
** updatable views will not be supported
* make sure views show up anywhere tables can currently be enumerated/searched
* where relevant, provide additional metadata to allow views to be 
distinguished from tables

Beyond this, we may want to

* expose metadata about view definitions and dependencies (at table-level or 
column-level) in a way that makes them consumable by metadata-driven tools

= Implementation Sketch =

The basics of view implementation are very easy due to the fact that Hive 
already supports subselects in the FROM clause.

* For <b>CREATE VIEW v AS view-def-select</b>, we extend SemanticAnalyzer to 
behave similarly to <b>CREATE TABLE t AS select</b>, except that we don't 
actually execute the query (we stop after plan generation).  It's necessary to 
perform all of plan generation (even though we're not actually going to execute 
the plan) since currently some validations such as type compatibility-checking 
are only performed during plan generation.  After successful validation, the 
text of the view is saved in the metastore (the simplest approach snips out the 
text from the parser's token stream, but this approach introduces problems 
described in the issues section below).
* For <b>select ... from view-reference</b>, we detect the view reference in 
SemanticAnalyzer.getMetaData, load the text of its definition from the 
metastore, parse it back into an AST, prepare a QBExpr to hold it, and then 
plug this into the referencing query's QB, resulting in a tree equivalent to 
<b>select ... from (view-def-select)</b>; plan generation can then be carried 
out on the combined tree.

= Issues =

Some of these are related to functionality/scope; others are related to 
implementation approaches.  Opinions are welcome on all of them.

== Stored View Definition ==

In SQL:200n, a view definition is supposed to be frozen at the time it is 
created, so that if the view is defined as select * from t, where t is a table 
with two columns a and b, then later requests to select * from the view should 
return just columns a and b, even if a new column c is later added to the 
table.  This is implemented correctly by most DBMS products.

There are similar issues with other kinds of references in the view definition; 
for example, if a table or function name can be qualified, then the reference 
should be bound at the time the view is created.

Implementing this typically requires expanding the view definition into an 
explicit form rather than storing the original view definition text directly.  
Doing this could require adding "unparse" support to the AST model (to be 
applied after object name resolution takes place), something which is not 
currently present (and which is also useful to have available in general).

== Metastore Modeling ==

The metastore model will need to be augmented in order to allow view 
definitions to be saved.  An important issue to be resolved is whether to model 
this via inheritance, or just shoehorn views in as a special kind of table.

With an inheritance model, views and base tables would share a common base 
class (here called ColumnSet following the convention in the Common Warehouse 
Metamodel for lack of a better term):

[[Image:Data--Hive--ViewDev--HiveViewInheritance.png]]

For a view, most of the storage descriptor (everything other than the column 
names and types) would be irrelevant, so this model could be further refined 
with such discriminations.

View names and table names share the same namespace with respect to uniqueness 
(i.e. you can't have a table and a view with the same name), so the name key 
uniqueness would need to be specified at the base class level.

Alternately, if we choose to avoid inheritance, then we could just add a new 
viewText attribute to the existing Table class (leaving it null for base 
tables):

[[Image:Data--Hive--ViewDev--HiveViewFlat.png]]

(Storing the view definition as a table property may not work since property 
values are limited to VARCHAR(767), and view definitions may be much longer 
than that, so we'll need to use a LOB.)

Comparison of the two approaches:

{| border="1"
|-
! 
! Inheritance Model
! Flat Model
|-
! JDO Support
| Need to investigate how well inheritance works for our purposes
| Nothing special
|-
! Metadata queries from existing code/tools
| Existing queries for tables will NOT include views in results; those that 
need to will have to be modified to reference base class instead
| Existing queries for tables WILL include views in results; those that are not 
supposed to will need to filter them out
|-
! Metastore upgrade on deployment
| Need to test carefully to make sure introducing inheritance doesn't corrupt 
existing metastore instances
| Nothing special, just adding a new attribute
|}

== Dependency Tracking ==

It's necessary to track dependencies from a view to objects it references in 
the metastore:

* tables:  this is mandatory if we want DROP TABLE to be able to correctly 
CASCADE/RESTRICT to a referencing view
* other views:  same as tables
* columns:  this is optional (useful for lineage inspection, but not required 
for implementing SQL features)
* temporary functions:  we should disallow these at view creation unless we 
also want a concept of temporary view (or if it's OK for the referencing view 
to become invalid whenever the volatile function registry gets cleared)
* any other objects? (e.g. udt's coming in as part of 
[http://issues.apache.org/jira/browse/HIVE-779 HIVE-779])

(Note that MySQL doesn't actually implement CASCADE/RESTRICT:  it just ignores 
the keyword and drops the table unconditionally, leaving the view dangling.)

Metastore object id's can be used for dependency modeling in order to avoid the 
need to update dependency records when an object is renamed.  However, we'll 
need to decide what kinds of objects can participate in dependencies.  For 
example, if we restrict it to just tables and views (and assuming we don't 
introduce inheritance for views), then we can use a model like the one below, 
in which the dependencies are tracked as (supplier,consumer) table pairs.  (In 
this model, the TableDependency class is acting as an intersection table for 
implementing a many-to-many relationship between suppliers and consumers).

[[Image:Data--Hive--ViewDev--HiveTableDependency.png]]

However, if later we want to introduce persistent functions, or track column 
dependencies, this model will be insufficient, and we may need to introduce 
inheritance, with a DependencyParticipant base class from which tables, 
columns, functions etc all derive.  (Again, need to verify that JDO inheritance 
will actually support what we want here.)

== Dependency Invalidation ==

What happens when an object is modified underneath a view?  For example, 
suppose a view references a table's column, and then ALTER TABLE is used to 
drop or replace that column.  Note that if the column's datatype changes, the 
view definition may remain meaningful, but the view's schema may need to be 
updated to match.  Here are two possible options:

* <b>Strict</b>:  prevent operations which would invalidate or change the view 
in any way (and optionally to provide a CASCADE flag which requests that such 
views be dropped automatically).  This is the approach taken by SQL:200n.
* <b>Lenient</b>: allow the update to proceed (and maybe warn the user of the 
impact), potentially leaving the view in an invalid state.  Later, when an 
invalid view definition is referenced, throw a validation exception for the 
referencing query.  This is the approach taken by MySQL.  In the case of 
datatype changes, derived column datatypes already stored in metastore for 
referencing views would become stale until those views were recreated.

Note that besides table modifications, other operations such as CREATE OR 
REPLACE VIEW have similar issues (since views can reference other views).  The 
lenient approach provides a reasonable solution for the related issue of 
external tables whose schemas may be dynamic (not sure if we currently support 
this).

== View Modification ==

In SQL:200n, there's no standard way to update a view definition.  MySQL 
supports both

* <b>CREATE OR REPLACE VIEW v AS new-view-def-select</b>
* <b>ALTER VIEW v AS new-view-def-select</b>

Note that supporting view modification requires detection of cyclic view 
definitions, which should be invalid.  Whether this detection is carried out at 
the time of view modification versus reference is dependent on the strict 
versus lenient approaches to dependency invalidation described above.

== Fast Path Execution ==

For <b>select * from t</b>, hive supports fast-path execution (skipping 
Map/Reduce).  Is it important for this to work for <b>select * from v</b> as 
well?

== ORDER BY and LIMIT in view definition ==

SQL:200n prohibits ORDER BY in a view definition, since a view is supposed to 
be a virtual (unordered) table, not a query alias.  However, many DBMS's ignore 
this rule; for example, MySQL allows ORDER BY, but ignores it in the case where 
it is superceded by an ORDER BY in the query.  Should we prevent ORDER BY?  
This question also applies to the LIMIT clause.

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