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Summary of changes:
1) Simplified type system. The old system was overly complicated for
the task of query generation. The modeling of types used to mirror
the types used in Impala. For simplicity, new system only uses a
subset of types, Boolean, Char, Decimal, Float, Int, and Timestamp.
2) Functions now have fully typed signatures. Previously you had to
know which functions accepted which inputs, now arbitrary
permutations of functions can be generated. The chance of being
able to add a new function without needing to change the query
generation logic is much higher now.
3) Query generation profiles. The randomness of the previous version
was hardcoded in various places in throughout the query generator.
Now there is a profile to determine which SQL features should be
used. There is still a lot of room for improvement in terms of
intuitiveness and documentation for configuring the profiles.
4) Greater diversity of queries. Besides the function permutations,
various restrictions to simplify query generation have been
removed. Also constants are used in queries.
5) Eliminate spinning and infinite loops. Also the old version would
sometimes "hope" that a generated SQL element would be compatible
with the context and if not, it would try again which would lead
to noticeable spinning and/or infinite loops.
6) Catchup with Impala 2.0 features: subqueries, analytics, and
Char/VarChar.
Change-Id: Ia25f4e85d6a06f7958a906aa42d9f90d63675bc0
Reviewed-on: http://gerrit.sjc.cloudera.com:8080/5640
Reviewed-by: Casey Ching <casey@cloudera.com>
Tested-by: jenkins
389 lines
12 KiB
Python
389 lines
12 KiB
Python
# Copyright (c) 2014 Cloudera, Inc. All rights reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from collections import defaultdict
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from copy import deepcopy
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# The model related modules (types.py, query.py, etc) are interconnected by circular
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# imports which causes problems for the python import system. This module is intended to
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# be the first of the circular modules imported. To be importable, no direct references
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# are made to the other modules from this modules namespace. Instead, other modules are
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# lazyily imported using the following function. Keep in mind that python "globals" are
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# module local, there is no such thing as a cross-module global.
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__ALREADY_IMPORTED = False
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def get_import(name):
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global __ALREADY_IMPORTED
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if not __ALREADY_IMPORTED:
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from tests.comparison.types import (
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Boolean,
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Char,
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DataType,
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Float,
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Int,
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JOINABLE_TYPES,
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Number,
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Timestamp)
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from tests.comparison.funcs import AggFunc, AnalyticFunc, Func
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from tests.comparison.query import InlineView, Subquery, WithClauseInlineView
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for key, value in locals().items():
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globals()[key] = value
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__ALREADY_IMPORTED = True
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return globals()[name]
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class ValExpr(object):
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'''This is class that represents a generic expr that results in a scalar.'''
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@property
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def type(self):
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'''Returns the type that this expr evaluates to. The type may be Int or Char but
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never BigInt or String. Valid return value are the set defined in types.TYPES.
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'''
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return self.exact_type.get_generic_type()
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@property
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def exact_type(self):
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'''Return the actual type of the val expr. For example "type" could return Int and
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"exact_type" could return TinyInt.
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'''
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pass
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@property
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def base_type(self):
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'''Returns the lowest type in the type heirarchy that is not DataType. For non-
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numeric types, the return value will be the same is self.type. Numeric types
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will return Number whereas self.type may be Decimal, Int, or Float.
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'''
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return self.type.get_base_type()
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@property
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def is_func(self):
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'''Evaluates to True if this expr is an instance of a function.'''
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return isinstance(self, get_import('Func'))
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@property
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def is_agg(self):
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'''Evaluates to True if this expr is an instance of an aggregate function.'''
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return isinstance(self, get_import('AggFunc'))
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@property
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def is_analytic(self):
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'''Evaluates to True if this expr is an instance of an analytic function.'''
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return isinstance(self, get_import('AnalyticFunc'))
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@property
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def contains_agg(self):
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'''Evaluates to True if this expression is an aggregate function or contains an
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aggregate function.
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'''
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if self.is_agg:
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return True
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return any(isinstance(arg, ValExpr) and arg.contains_agg for arg in self.args)
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@property
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def contains_analytic(self):
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'''Evaluates to True if this expression is an analytic function or contains an
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analytic function.
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'''
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if self.is_analytic:
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return True
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if self.is_func:
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for arg in self.args:
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if isinstance(arg, ValExpr) and arg.contains_analytic:
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return True
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@property
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def contains_subquery(self):
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'''Evaluates to True if this expression is a subquery or contains a subquery.'''
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if self.is_subquery:
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return True
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if self.is_func:
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for arg in self.args:
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if isinstance(arg, ValExpr) and arg.contains_subquery:
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return True
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@property
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def is_col(self):
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return isinstance(self, Column)
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@property
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def is_constant(self):
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return isinstance(self, get_import('DataType'))
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@property
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def is_subquery(self):
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return isinstance(self, get_import('Subquery'))
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@property
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def returns_boolean(self):
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return issubclass(self.type, get_import('Boolean'))
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@property
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def returns_int(self):
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return issubclass(self.type, get_import('Int'))
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@property
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def returns_float(self):
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return issubclass(self.type, get_import('Float'))
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@property
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def returns_char(self):
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return issubclass(self.type, get_import('Char'))
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@property
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def returns_timestamp(self):
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return issubclass(self.type, get_import('Timestamp'))
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def iter_exprs(self, filter=None):
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'''Return an iterator over all exprs that this expr contains as a function argument
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including this expr itself.
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'''
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if not filter or filter(self):
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yield self
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def count_col_refs(self):
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'''Return a dict with Columns as keys and the number of times the column was used
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in this expr as values.
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'''
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col_ref_counts = defaultdict(int)
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if self.is_func:
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for arg in self.args:
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if isinstance(arg, ValExpr):
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for col, count in arg.count_col_refs().iteritems():
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col_ref_counts[col] += count
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elif self.is_col:
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col_ref_counts[self] += 1
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return col_ref_counts
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class Column(ValExpr):
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'''A representation of a column. All TableExprs will have Columns. So a Column
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may belong to an InlineView as well as a standard Table.
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This class is used in two ways:
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1) As a piece of metadata in a table definiton. In this usage the col isn't
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intended to represent an val.
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2) As an expr in a query, for example an item being selected or as part of
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a JOIN condition. In this usage the col is more like a val, which is why
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it implements/extends ValExpr.
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'''
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def __init__(self, owner, name, exact_type):
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self.owner = owner
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self.name = name
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self._exact_type = exact_type
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@property
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def exact_type(self):
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return self._exact_type
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@exact_type.setter
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def exact_type(self, exact_type):
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self._exact_type = exact_type
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def __hash__(self):
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return hash(self.name)
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def __eq__(self, other):
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if not isinstance(other, Column):
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return False
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if self is other:
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return True
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return self.name == other.name and self.owner.identifier == other.owner.identifier
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def __repr__(self):
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return '%s<name: %s, type: %s>' % (
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type(self).__name__, self.name, self.type.__name__)
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def __deepcopy__(self, memo):
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# Don't return a deep copy of owner, since that is a circular reference
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return Column(self.owner, self.name, self.exact_type)
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class ValExprList(list):
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'''A list of ValExprs'''
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@property
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def by_type(self):
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return get_import('DataType').group_by_type(self)
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class TableExpr(object):
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'''This class represents something that a query may use to SELECT from or JOIN on.'''
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def identifier(self):
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'''Returns either a table name or alias if one has been declared.'''
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pass
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def cols(self):
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pass
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@property
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def unique_cols(self):
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'''Returns a list of lists of Cols that in combination define a unique set of values
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within the table. The returned list could be thought of as a list of uniqueness
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constraints (though there may be no actual constraints or any other type of
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enforcement).
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'''
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return ValExprList()
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@property
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def joinable_cols(self):
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'''Returns a list of Cols that are of a type that is allowed in a JOIN. This is
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mostly an Impala specific thing since Impala requires at least one equality based
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join and not all types are allowed in equality comparisons. Also Boolean is
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excluded because of low cardinality.
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'''
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joinable_types = tuple(get_import('JOINABLE_TYPES'))
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return ValExprList(col for col in self.cols if issubclass(col.type, joinable_types))
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@property
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def col_types(self):
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'''Returns a Set containing the various column types that this TableExpr contains.'''
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return set(self.cols_by_type)
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def is_visible(self):
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'''If False is returned, columns from this TableExpr may only be used in JOIN
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conditions. This is intended to be used to identify ANTI and SEMI joined table
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exprs.
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'''
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pass
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@property
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def cols_by_type(self):
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'''Group cols of the same type into lists and return a dict of the results.'''
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return get_import('DataType').group_by_type(self.cols)
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@property
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def joinable_cols_by_type(self):
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return get_import('DataType').group_by_type(self.joinable_cols)
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@property
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def is_table(self):
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return isinstance(self, Table)
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@property
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def is_inline_view(self):
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return isinstance(self, get_import('InlineView'))
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@property
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def is_with_clause_inline_view(self):
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return isinstance(self, get_import('WithClauseInlineView'))
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def __eq__(self, other):
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if not isinstance(other, type(self)):
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return False
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return self.identifier == other.identifier
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class Table(TableExpr):
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'''Represents a standard database table.'''
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def __init__(self, name):
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self.name = name
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self._cols = ValExprList()
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self._unique_cols = ValExprList()
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self.alias = None
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self.is_visible = True # tables used in SEMI or ANTI JOINs are invisible
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@property
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def identifier(self):
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return self.alias or self.name
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@property
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def cols(self):
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return self._cols
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@cols.setter
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def cols(self, cols):
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self._cols = cols
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@property
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def unique_cols(self):
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return self._unique_cols
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@unique_cols.setter
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def unique_cols(self, unique_cols):
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self._unique_cols = unique_cols
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def __repr__(self):
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return 'Table<name: %s, cols: %s>' \
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% (self.name, ', '.join([str(col) for col in self.cols]))
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def __deepcopy__(self, memo):
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other = Table(self.name)
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other.alias = self.alias
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other.is_visible = self.is_visible
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cols_by_name = dict()
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# Copy the cols and set their owner to the copy of the TableExpr
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for col in self._cols:
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col = deepcopy(col, memo)
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col.owner = other
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cols_by_name[col.name] = col
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other._cols = ValExprList(cols_by_name[col.name] for col in self._cols)
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other._unique_cols = ValExprList()
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for col_combo in self._unique_cols:
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other_col_combo = set()
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for col in col_combo:
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if col.name in cols_by_name:
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col = cols_by_name[col.name]
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else:
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col = deepcopy(col, memo)
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col.owner = other
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other_col_combo.add(col)
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other.unique_cols.append(other_col_combo)
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return other
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class TableExprList(list):
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'''A list of TableExprs.'''
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@property
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def cols(self):
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'''Return a list of all the Columns containd in all the TableExprs.'''
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return ValExprList(col for table_expr in self for col in table_expr.cols)
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@property
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def joinable_cols_by_type(self):
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cols_by_type = defaultdict(ValExprList)
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for table_expr in self:
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for type_, cols in table_expr.joinable_cols_by_type.iteritems():
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cols_by_type[type_].extend(cols)
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return cols_by_type
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@property
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def cols_by_type(self):
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cols_by_type = defaultdict(ValExprList)
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for table_expr in self:
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for type_, cols in table_expr.cols_by_type.iteritems():
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cols_by_type[type_].extend(cols)
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return cols_by_type
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@property
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def col_types(self):
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return tuple(self.cols_by_type)
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@property
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def by_col_type(self):
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'''Return a dict with keys being column types and values being lists of TableExprs
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that have at least one Column of that type.
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'''
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table_exprs_by_type = defaultdict(TableExprList)
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for table_expr in self:
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for col_type in table_expr.col_types:
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table_exprs_by_type[col_type].append(table_expr)
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return table_exprs_by_type
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