# Copyright 2013-2016 DataStax, Inc.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from bisect import bisect_right
from collections import defaultdict, Mapping
from hashlib import md5
from itertools import islice, cycle
import json
import logging
import re
import six
from six.moves import zip
import sys
from threading import RLock
murmur3 = None
try:
from cassandra.murmur3 import murmur3
except ImportError as e:
pass
from cassandra import SignatureDescriptor, ConsistencyLevel, InvalidRequest, Unauthorized
import cassandra.cqltypes as types
from cassandra.encoder import Encoder
from cassandra.marshal import varint_unpack
from cassandra.protocol import QueryMessage
from cassandra.query import dict_factory, bind_params
from cassandra.util import OrderedDict
log = logging.getLogger(__name__)
cql_keywords = set((
'add', 'aggregate', 'all', 'allow', 'alter', 'and', 'apply', 'as', 'asc', 'ascii', 'authorize', 'batch', 'begin',
'bigint', 'blob', 'boolean', 'by', 'called', 'clustering', 'columnfamily', 'compact', 'contains', 'count',
'counter', 'create', 'custom', 'date', 'decimal', 'delete', 'desc', 'describe', 'distinct', 'double', 'drop',
'entries', 'execute', 'exists', 'filtering', 'finalfunc', 'float', 'from', 'frozen', 'full', 'function',
'functions', 'grant', 'if', 'in', 'index', 'inet', 'infinity', 'initcond', 'input', 'insert', 'int', 'into', 'is', 'json',
'key', 'keys', 'keyspace', 'keyspaces', 'language', 'limit', 'list', 'login', 'map', 'materialized', 'modify', 'nan', 'nologin',
'norecursive', 'nosuperuser', 'not', 'null', 'of', 'on', 'options', 'or', 'order', 'password', 'permission',
'permissions', 'primary', 'rename', 'replace', 'returns', 'revoke', 'role', 'roles', 'schema', 'select', 'set',
'sfunc', 'smallint', 'static', 'storage', 'stype', 'superuser', 'table', 'text', 'time', 'timestamp', 'timeuuid',
'tinyint', 'to', 'token', 'trigger', 'truncate', 'ttl', 'tuple', 'type', 'unlogged', 'update', 'use', 'user',
'users', 'using', 'uuid', 'values', 'varchar', 'varint', 'view', 'where', 'with', 'writetime'
))
"""
Set of keywords in CQL.
Derived from .../cassandra/src/java/org/apache/cassandra/cql3/Cql.g
"""
cql_keywords_unreserved = set((
'aggregate', 'all', 'as', 'ascii', 'bigint', 'blob', 'boolean', 'called', 'clustering', 'compact', 'contains',
'count', 'counter', 'custom', 'date', 'decimal', 'distinct', 'double', 'exists', 'filtering', 'finalfunc', 'float',
'frozen', 'function', 'functions', 'inet', 'initcond', 'input', 'int', 'json', 'key', 'keys', 'keyspaces',
'language', 'list', 'login', 'map', 'nologin', 'nosuperuser', 'options', 'password', 'permission', 'permissions',
'returns', 'role', 'roles', 'sfunc', 'smallint', 'static', 'storage', 'stype', 'superuser', 'text', 'time',
'timestamp', 'timeuuid', 'tinyint', 'trigger', 'ttl', 'tuple', 'type', 'user', 'users', 'uuid', 'values', 'varchar',
'varint', 'writetime'
))
"""
Set of unreserved keywords in CQL.
Derived from .../cassandra/src/java/org/apache/cassandra/cql3/Cql.g
"""
cql_keywords_reserved = cql_keywords - cql_keywords_unreserved
"""
Set of reserved keywords in CQL.
"""
_encoder = Encoder()
REPLICATION_STRATEGY_CLASS_PREFIX = "org.apache.cassandra.locator."
def trim_if_startswith(s, prefix):
if s.startswith(prefix):
return s[len(prefix):]
return s
_replication_strategies = {}
class ReplicationStrategyTypeType(type):
def __new__(metacls, name, bases, dct):
dct.setdefault('name', name)
cls = type.__new__(metacls, name, bases, dct)
if not name.startswith('_'):
_replication_strategies[name] = cls
return cls
@six.add_metaclass(ReplicationStrategyTypeType)
class _ReplicationStrategy(object):
options_map = None
@classmethod
def create(cls, strategy_class, options_map):
if not strategy_class:
return None
strategy_name = trim_if_startswith(strategy_class, REPLICATION_STRATEGY_CLASS_PREFIX)
rs_class = _replication_strategies.get(strategy_name, None)
if rs_class is None:
rs_class = _UnknownStrategyBuilder(strategy_name)
_replication_strategies[strategy_name] = rs_class
try:
rs_instance = rs_class(options_map)
except Exception as exc:
log.warning("Failed creating %s with options %s: %s", strategy_name, options_map, exc)
return None
return rs_instance
def make_token_replica_map(self, token_to_host_owner, ring):
raise NotImplementedError()
def export_for_schema(self):
raise NotImplementedError()
ReplicationStrategy = _ReplicationStrategy
class _UnknownStrategyBuilder(object):
def __init__(self, name):
self.name = name
def __call__(self, options_map):
strategy_instance = _UnknownStrategy(self.name, options_map)
return strategy_instance
class _UnknownStrategy(ReplicationStrategy):
def __init__(self, name, options_map):
self.name = name
self.options_map = options_map.copy() if options_map is not None else dict()
self.options_map['class'] = self.name
def __eq__(self, other):
return (isinstance(other, _UnknownStrategy)
and self.name == other.name
and self.options_map == other.options_map)
def export_for_schema(self):
"""
Returns a string version of these replication options which are
suitable for use in a CREATE KEYSPACE statement.
"""
if self.options_map:
return dict((str(key), str(value)) for key, value in self.options_map.items())
return "{'class': '%s'}" % (self.name, )
def make_token_replica_map(self, token_to_host_owner, ring):
return {}
[docs]class SimpleStrategy(ReplicationStrategy):
replication_factor = None
"""
The replication factor for this keyspace.
"""
def __init__(self, options_map):
try:
self.replication_factor = int(options_map['replication_factor'])
except Exception:
raise ValueError("SimpleStrategy requires an integer 'replication_factor' option")
def make_token_replica_map(self, token_to_host_owner, ring):
replica_map = {}
for i in range(len(ring)):
j, hosts = 0, list()
while len(hosts) < self.replication_factor and j < len(ring):
token = ring[(i + j) % len(ring)]
host = token_to_host_owner[token]
if host not in hosts:
hosts.append(host)
j += 1
replica_map[ring[i]] = hosts
return replica_map
[docs] def export_for_schema(self):
"""
Returns a string version of these replication options which are
suitable for use in a CREATE KEYSPACE statement.
"""
return "{'class': 'SimpleStrategy', 'replication_factor': '%d'}" \
% (self.replication_factor,)
def __eq__(self, other):
if not isinstance(other, SimpleStrategy):
return False
return self.replication_factor == other.replication_factor
[docs]class NetworkTopologyStrategy(ReplicationStrategy):
dc_replication_factors = None
"""
A map of datacenter names to the replication factor for that DC.
"""
def __init__(self, dc_replication_factors):
self.dc_replication_factors = dict(
(str(k), int(v)) for k, v in dc_replication_factors.items())
def make_token_replica_map(self, token_to_host_owner, ring):
# note: this does not account for hosts having different racks
replica_map = defaultdict(list)
dc_rf_map = dict((dc, int(rf))
for dc, rf in self.dc_replication_factors.items() if rf > 0)
# build a map of DCs to lists of indexes into `ring` for tokens that
# belong to that DC
dc_to_token_offset = defaultdict(list)
dc_racks = defaultdict(set)
for i, token in enumerate(ring):
host = token_to_host_owner[token]
dc_to_token_offset[host.datacenter].append(i)
if host.datacenter and host.rack:
dc_racks[host.datacenter].add(host.rack)
# A map of DCs to an index into the dc_to_token_offset value for that dc.
# This is how we keep track of advancing around the ring for each DC.
dc_to_current_index = defaultdict(int)
for i in range(len(ring)):
replicas = replica_map[ring[i]]
# go through each DC and find the replicas in that DC
for dc in dc_to_token_offset.keys():
if dc not in dc_rf_map:
continue
# advance our per-DC index until we're up to at least the
# current token in the ring
token_offsets = dc_to_token_offset[dc]
index = dc_to_current_index[dc]
num_tokens = len(token_offsets)
while index < num_tokens and token_offsets[index] < i:
index += 1
dc_to_current_index[dc] = index
replicas_remaining = dc_rf_map[dc]
skipped_hosts = []
racks_placed = set()
racks_this_dc = dc_racks[dc]
for token_offset in islice(cycle(token_offsets), index, index + num_tokens):
host = token_to_host_owner[ring[token_offset]]
if replicas_remaining == 0:
break
if host in replicas:
continue
if host.rack in racks_placed and len(racks_placed) < len(racks_this_dc):
skipped_hosts.append(host)
continue
replicas.append(host)
replicas_remaining -= 1
racks_placed.add(host.rack)
if len(racks_placed) == len(racks_this_dc):
for host in skipped_hosts:
if replicas_remaining == 0:
break
replicas.append(host)
replicas_remaining -= 1
del skipped_hosts[:]
return replica_map
[docs] def export_for_schema(self):
"""
Returns a string version of these replication options which are
suitable for use in a CREATE KEYSPACE statement.
"""
ret = "{'class': 'NetworkTopologyStrategy'"
for dc, repl_factor in sorted(self.dc_replication_factors.items()):
ret += ", '%s': '%d'" % (dc, repl_factor)
return ret + "}"
def __eq__(self, other):
if not isinstance(other, NetworkTopologyStrategy):
return False
return self.dc_replication_factors == other.dc_replication_factors
[docs]class LocalStrategy(ReplicationStrategy):
def __init__(self, options_map):
pass
def make_token_replica_map(self, token_to_host_owner, ring):
return {}
[docs] def export_for_schema(self):
"""
Returns a string version of these replication options which are
suitable for use in a CREATE KEYSPACE statement.
"""
return "{'class': 'LocalStrategy'}"
def __eq__(self, other):
return isinstance(other, LocalStrategy)
[docs]class UserType(object):
"""
A user defined type, as created by ``CREATE TYPE`` statements.
User-defined types were introduced in Cassandra 2.1.
.. versionadded:: 2.1.0
"""
keyspace = None
"""
The string name of the keyspace in which this type is defined.
"""
name = None
"""
The name of this type.
"""
field_names = None
"""
An ordered list of the names for each field in this user-defined type.
"""
field_types = None
"""
An ordered list of the types for each field in this user-defined type.
"""
def __init__(self, keyspace, name, field_names, field_types):
self.keyspace = keyspace
self.name = name
# non-frozen collections can return None
self.field_names = field_names or []
self.field_types = field_types or []
[docs] def as_cql_query(self, formatted=False):
"""
Returns a CQL query that can be used to recreate this type.
If `formatted` is set to :const:`True`, extra whitespace will
be added to make the query more readable.
"""
ret = "CREATE TYPE %s.%s (%s" % (
protect_name(self.keyspace),
protect_name(self.name),
"\n" if formatted else "")
if formatted:
field_join = ",\n"
padding = " "
else:
field_join = ", "
padding = ""
fields = []
for field_name, field_type in zip(self.field_names, self.field_types):
fields.append("%s %s" % (protect_name(field_name), field_type))
ret += field_join.join("%s%s" % (padding, field) for field in fields)
ret += "\n)" if formatted else ")"
return ret
def export_as_string(self):
return self.as_cql_query(formatted=True) + ';'
[docs]class Aggregate(object):
"""
A user defined aggregate function, as created by ``CREATE AGGREGATE`` statements.
Aggregate functions were introduced in Cassandra 2.2
.. versionadded:: 2.6.0
"""
keyspace = None
"""
The string name of the keyspace in which this aggregate is defined
"""
name = None
"""
The name of this aggregate
"""
argument_types = None
"""
An ordered list of the types for each argument to the aggregate
"""
final_func = None
"""
Name of a final function
"""
initial_condition = None
"""
Initial condition of the aggregate
"""
return_type = None
"""
Return type of the aggregate
"""
state_func = None
"""
Name of a state function
"""
state_type = None
"""
Type of the aggregate state
"""
def __init__(self, keyspace, name, argument_types, state_func,
state_type, final_func, initial_condition, return_type):
self.keyspace = keyspace
self.name = name
self.argument_types = argument_types
self.state_func = state_func
self.state_type = state_type
self.final_func = final_func
self.initial_condition = initial_condition
self.return_type = return_type
[docs] def as_cql_query(self, formatted=False):
"""
Returns a CQL query that can be used to recreate this aggregate.
If `formatted` is set to :const:`True`, extra whitespace will
be added to make the query more readable.
"""
sep = '\n ' if formatted else ' '
keyspace = protect_name(self.keyspace)
name = protect_name(self.name)
type_list = ', '.join(self.argument_types)
state_func = protect_name(self.state_func)
state_type = self.state_type
ret = "CREATE AGGREGATE %(keyspace)s.%(name)s(%(type_list)s)%(sep)s" \
"SFUNC %(state_func)s%(sep)s" \
"STYPE %(state_type)s" % locals()
ret += ''.join((sep, 'FINALFUNC ', protect_name(self.final_func))) if self.final_func else ''
ret += ''.join((sep, 'INITCOND ', self.initial_condition)) if self.initial_condition is not None else ''
return ret
def export_as_string(self):
return self.as_cql_query(formatted=True) + ';'
@property
def signature(self):
return SignatureDescriptor.format_signature(self.name, self.argument_types)
[docs]class Function(object):
"""
A user defined function, as created by ``CREATE FUNCTION`` statements.
User-defined functions were introduced in Cassandra 2.2
.. versionadded:: 2.6.0
"""
keyspace = None
"""
The string name of the keyspace in which this function is defined
"""
name = None
"""
The name of this function
"""
argument_types = None
"""
An ordered list of the types for each argument to the function
"""
argument_names = None
"""
An ordered list of the names of each argument to the function
"""
return_type = None
"""
Return type of the function
"""
language = None
"""
Language of the function body
"""
body = None
"""
Function body string
"""
called_on_null_input = None
"""
Flag indicating whether this function should be called for rows with null values
(convenience function to avoid handling nulls explicitly if the result will just be null)
"""
def __init__(self, keyspace, name, argument_types, argument_names,
return_type, language, body, called_on_null_input):
self.keyspace = keyspace
self.name = name
self.argument_types = argument_types
# argument_types (frozen<list<>>) will always be a list
# argument_name is not frozen in C* < 3.0 and may return None
self.argument_names = argument_names or []
self.return_type = return_type
self.language = language
self.body = body
self.called_on_null_input = called_on_null_input
[docs] def as_cql_query(self, formatted=False):
"""
Returns a CQL query that can be used to recreate this function.
If `formatted` is set to :const:`True`, extra whitespace will
be added to make the query more readable.
"""
sep = '\n ' if formatted else ' '
keyspace = protect_name(self.keyspace)
name = protect_name(self.name)
arg_list = ', '.join(["%s %s" % (protect_name(n), t)
for n, t in zip(self.argument_names, self.argument_types)])
typ = self.return_type
lang = self.language
body = self.body
on_null = "CALLED" if self.called_on_null_input else "RETURNS NULL"
return "CREATE FUNCTION %(keyspace)s.%(name)s(%(arg_list)s)%(sep)s" \
"%(on_null)s ON NULL INPUT%(sep)s" \
"RETURNS %(typ)s%(sep)s" \
"LANGUAGE %(lang)s%(sep)s" \
"AS $$%(body)s$$" % locals()
def export_as_string(self):
return self.as_cql_query(formatted=True) + ';'
@property
def signature(self):
return SignatureDescriptor.format_signature(self.name, self.argument_types)
if six.PY3:
def protect_name(name):
return maybe_escape_name(name)
else:
def protect_name(name): # NOQA
if isinstance(name, six.text_type):
name = name.encode('utf8')
return maybe_escape_name(name)
def protect_names(names):
return [protect_name(n) for n in names]
def protect_value(value):
if value is None:
return 'NULL'
if isinstance(value, (int, float, bool)):
return str(value).lower()
return "'%s'" % value.replace("'", "''")
valid_cql3_word_re = re.compile(r'^[a-z][0-9a-z_]*$')
def is_valid_name(name):
if name is None:
return False
if name.lower() in cql_keywords_reserved:
return False
return valid_cql3_word_re.match(name) is not None
def maybe_escape_name(name):
if is_valid_name(name):
return name
return escape_name(name)
def escape_name(name):
return '"%s"' % (name.replace('"', '""'),)
[docs]class TokenMap(object):
"""
Information about the layout of the ring.
"""
token_class = None
"""
A subclass of :class:`.Token`, depending on what partitioner the cluster uses.
"""
token_to_host_owner = None
"""
A map of :class:`.Token` objects to the :class:`.Host` that owns that token.
"""
tokens_to_hosts_by_ks = None
"""
A map of keyspace names to a nested map of :class:`.Token` objects to
sets of :class:`.Host` objects.
"""
ring = None
"""
An ordered list of :class:`.Token` instances in the ring.
"""
_metadata = None
def __init__(self, token_class, token_to_host_owner, all_tokens, metadata):
self.token_class = token_class
self.ring = all_tokens
self.token_to_host_owner = token_to_host_owner
self.tokens_to_hosts_by_ks = {}
self._metadata = metadata
self._rebuild_lock = RLock()
def rebuild_keyspace(self, keyspace, build_if_absent=False):
with self._rebuild_lock:
current = self.tokens_to_hosts_by_ks.get(keyspace, None)
if (build_if_absent and current is None) or (not build_if_absent and current is not None):
ks_meta = self._metadata.keyspaces.get(keyspace)
if ks_meta:
replica_map = self.replica_map_for_keyspace(self._metadata.keyspaces[keyspace])
self.tokens_to_hosts_by_ks[keyspace] = replica_map
def replica_map_for_keyspace(self, ks_metadata):
strategy = ks_metadata.replication_strategy
if strategy:
return strategy.make_token_replica_map(self.token_to_host_owner, self.ring)
else:
return None
def remove_keyspace(self, keyspace):
self.tokens_to_hosts_by_ks.pop(keyspace, None)
[docs] def get_replicas(self, keyspace, token):
"""
Get a set of :class:`.Host` instances representing all of the
replica nodes for a given :class:`.Token`.
"""
tokens_to_hosts = self.tokens_to_hosts_by_ks.get(keyspace, None)
if tokens_to_hosts is None:
self.rebuild_keyspace(keyspace, build_if_absent=True)
tokens_to_hosts = self.tokens_to_hosts_by_ks.get(keyspace, None)
if tokens_to_hosts:
# token range ownership is exclusive on the LHS (the start token), so
# we use bisect_right, which, in the case of a tie/exact match,
# picks an insertion point to the right of the existing match
point = bisect_right(self.ring, token)
if point == len(self.ring):
return tokens_to_hosts[self.ring[0]]
else:
return tokens_to_hosts[self.ring[point]]
return []
[docs]class Token(object):
"""
Abstract class representing a token.
"""
@classmethod
def hash_fn(cls, key):
return key
@classmethod
def from_key(cls, key):
return cls(cls.hash_fn(key))
def __cmp__(self, other):
if self.value < other.value:
return -1
elif self.value == other.value:
return 0
else:
return 1
def __eq__(self, other):
return self.value == other.value
def __lt__(self, other):
return self.value < other.value
def __hash__(self):
return hash(self.value)
def __repr__(self):
return "<%s: %s>" % (self.__class__.__name__, self.value)
__str__ = __repr__
MIN_LONG = -(2 ** 63)
MAX_LONG = (2 ** 63) - 1
class NoMurmur3(Exception):
pass
[docs]class Murmur3Token(Token):
"""
A token for ``Murmur3Partitioner``.
"""
@classmethod
def hash_fn(cls, key):
if murmur3 is not None:
h = int(murmur3(key))
return h if h != MIN_LONG else MAX_LONG
else:
raise NoMurmur3()
def __init__(self, token):
""" `token` should be an int or string representing the token. """
self.value = int(token)
[docs]class MD5Token(Token):
"""
A token for ``RandomPartitioner``.
"""
@classmethod
def hash_fn(cls, key):
if isinstance(key, six.text_type):
key = key.encode('UTF-8')
return abs(varint_unpack(md5(key).digest()))
def __init__(self, token):
""" `token` should be an int or string representing the token. """
self.value = int(token)
[docs]class BytesToken(Token):
"""
A token for ``ByteOrderedPartitioner``.
"""
def __init__(self, token_string):
""" `token_string` should be string representing the token. """
if not isinstance(token_string, six.string_types):
raise TypeError(
"Tokens for ByteOrderedPartitioner should be strings (got %s)"
% (type(token_string),))
self.value = token_string
class TriggerMetadata(object):
"""
A representation of a trigger for a table.
"""
table = None
""" The :class:`.TableMetadata` this trigger belongs to. """
name = None
""" The string name of this trigger. """
options = None
"""
A dict mapping trigger option names to their specific settings for this
table.
"""
def __init__(self, table_metadata, trigger_name, options=None):
self.table = table_metadata
self.name = trigger_name
self.options = options
def as_cql_query(self):
ret = "CREATE TRIGGER %s ON %s.%s USING %s" % (
protect_name(self.name),
protect_name(self.table.keyspace_name),
protect_name(self.table.name),
protect_value(self.options['class'])
)
return ret
def export_as_string(self):
return self.as_cql_query() + ';'
class _SchemaParser(object):
def __init__(self, connection, timeout):
self.connection = connection
self.timeout = timeout
def _handle_results(self, success, result):
if success:
return dict_factory(*result.results) if result else []
else:
raise result
def _query_build_row(self, query_string, build_func):
query = QueryMessage(query=query_string, consistency_level=ConsistencyLevel.ONE)
response = self.connection.wait_for_response(query, self.timeout)
result = dict_factory(*response.results)
if result:
return build_func(result[0])
class SchemaParserV22(_SchemaParser):
_SELECT_KEYSPACES = "SELECT * FROM system.schema_keyspaces"
_SELECT_COLUMN_FAMILIES = "SELECT * FROM system.schema_columnfamilies"
_SELECT_COLUMNS = "SELECT * FROM system.schema_columns"
_SELECT_TRIGGERS = "SELECT * FROM system.schema_triggers"
_SELECT_TYPES = "SELECT * FROM system.schema_usertypes"
_SELECT_FUNCTIONS = "SELECT * FROM system.schema_functions"
_SELECT_AGGREGATES = "SELECT * FROM system.schema_aggregates"
_table_name_col = 'columnfamily_name'
_function_agg_arument_type_col = 'signature'
recognized_table_options = (
"comment",
"read_repair_chance",
"dclocal_read_repair_chance", # kept to be safe, but see _build_table_options()
"local_read_repair_chance",
"replicate_on_write",
"gc_grace_seconds",
"bloom_filter_fp_chance",
"caching",
"compaction_strategy_class",
"compaction_strategy_options",
"min_compaction_threshold",
"max_compaction_threshold",
"compression_parameters",
"min_index_interval",
"max_index_interval",
"index_interval",
"speculative_retry",
"rows_per_partition_to_cache",
"memtable_flush_period_in_ms",
"populate_io_cache_on_flush",
"compression",
"default_time_to_live")
def __init__(self, connection, timeout):
super(SchemaParserV22, self).__init__(connection, timeout)
self.keyspaces_result = []
self.tables_result = []
self.columns_result = []
self.triggers_result = []
self.types_result = []
self.functions_result = []
self.aggregates_result = []
self.keyspace_table_rows = defaultdict(list)
self.keyspace_table_col_rows = defaultdict(lambda: defaultdict(list))
self.keyspace_type_rows = defaultdict(list)
self.keyspace_func_rows = defaultdict(list)
self.keyspace_agg_rows = defaultdict(list)
self.keyspace_table_trigger_rows = defaultdict(lambda: defaultdict(list))
def get_all_keyspaces(self):
self._query_all()
for row in self.keyspaces_result:
keyspace_meta = self._build_keyspace_metadata(row)
try:
for table_row in self.keyspace_table_rows.get(keyspace_meta.name, []):
table_meta = self._build_table_metadata(table_row)
keyspace_meta._add_table_metadata(table_meta)
for usertype_row in self.keyspace_type_rows.get(keyspace_meta.name, []):
usertype = self._build_user_type(usertype_row)
keyspace_meta.user_types[usertype.name] = usertype
for fn_row in self.keyspace_func_rows.get(keyspace_meta.name, []):
fn = self._build_function(fn_row)
keyspace_meta.functions[fn.signature] = fn
for agg_row in self.keyspace_agg_rows.get(keyspace_meta.name, []):
agg = self._build_aggregate(agg_row)
keyspace_meta.aggregates[agg.signature] = agg
except Exception:
log.exception("Error while parsing metadata for keyspace %s. Metadata model will be incomplete.", keyspace_meta.name)
keyspace_meta._exc_info = sys.exc_info()
yield keyspace_meta
def get_table(self, keyspaces, keyspace, table):
cl = ConsistencyLevel.ONE
where_clause = bind_params(" WHERE keyspace_name = %%s AND %s = %%s" % (self._table_name_col,), (keyspace, table), _encoder)
cf_query = QueryMessage(query=self._SELECT_COLUMN_FAMILIES + where_clause, consistency_level=cl)
col_query = QueryMessage(query=self._SELECT_COLUMNS + where_clause, consistency_level=cl)
triggers_query = QueryMessage(query=self._SELECT_TRIGGERS + where_clause, consistency_level=cl)
(cf_success, cf_result), (col_success, col_result), (triggers_success, triggers_result) \
= self.connection.wait_for_responses(cf_query, col_query, triggers_query, timeout=self.timeout, fail_on_error=False)
table_result = self._handle_results(cf_success, cf_result)
col_result = self._handle_results(col_success, col_result)
# handle the triggers table not existing in Cassandra 1.2
if not triggers_success and isinstance(triggers_result, InvalidRequest):
triggers_result = []
else:
triggers_result = self._handle_results(triggers_success, triggers_result)
if table_result:
return self._build_table_metadata(table_result[0], col_result, triggers_result)
def get_type(self, keyspaces, keyspace, type):
where_clause = bind_params(" WHERE keyspace_name = %s AND type_name = %s", (keyspace, type), _encoder)
return self._query_build_row(self._SELECT_TYPES + where_clause, self._build_user_type)
def get_function(self, keyspaces, keyspace, function):
where_clause = bind_params(" WHERE keyspace_name = %%s AND function_name = %%s AND %s = %%s" % (self._function_agg_arument_type_col,),
(keyspace, function.name, function.argument_types), _encoder)
return self._query_build_row(self._SELECT_FUNCTIONS + where_clause, self._build_function)
def get_aggregate(self, keyspaces, keyspace, aggregate):
where_clause = bind_params(" WHERE keyspace_name = %%s AND aggregate_name = %%s AND %s = %%s" % (self._function_agg_arument_type_col,),
(keyspace, aggregate.name, aggregate.argument_types), _encoder)
return self._query_build_row(self._SELECT_AGGREGATES + where_clause, self._build_aggregate)
def get_keyspace(self, keyspaces, keyspace):
where_clause = bind_params(" WHERE keyspace_name = %s", (keyspace,), _encoder)
return self._query_build_row(self._SELECT_KEYSPACES + where_clause, self._build_keyspace_metadata)
@classmethod
def _build_keyspace_metadata(cls, row):
try:
ksm = cls._build_keyspace_metadata_internal(row)
except Exception:
name = row["keyspace_name"]
ksm = KeyspaceMetadata(name, False, 'UNKNOWN', {})
ksm._exc_info = sys.exc_info() # capture exc_info before log because nose (test) logging clears it in certain circumstances
log.exception("Error while parsing metadata for keyspace %s row(%s)", name, row)
return ksm
@staticmethod
def _build_keyspace_metadata_internal(row):
name = row["keyspace_name"]
durable_writes = row["durable_writes"]
strategy_class = row["strategy_class"]
strategy_options = json.loads(row["strategy_options"])
return KeyspaceMetadata(name, durable_writes, strategy_class, strategy_options)
@classmethod
def _build_user_type(cls, usertype_row):
field_types = list(map(cls._schema_type_to_cql, usertype_row['field_types']))
return UserType(usertype_row['keyspace_name'], usertype_row['type_name'],
usertype_row['field_names'], field_types)
@classmethod
def _build_function(cls, function_row):
return_type = cls._schema_type_to_cql(function_row['return_type'])
return Function(function_row['keyspace_name'], function_row['function_name'],
function_row[cls._function_agg_arument_type_col], function_row['argument_names'],
return_type, function_row['language'], function_row['body'],
function_row['called_on_null_input'])
@classmethod
def _build_aggregate(cls, aggregate_row):
cass_state_type = types.lookup_casstype(aggregate_row['state_type'])
initial_condition = aggregate_row['initcond']
if initial_condition is not None:
initial_condition = _encoder.cql_encode_all_types(cass_state_type.deserialize(initial_condition, 3))
state_type = _cql_from_cass_type(cass_state_type)
return_type = cls._schema_type_to_cql(aggregate_row['return_type'])
return Aggregate(aggregate_row['keyspace_name'], aggregate_row['aggregate_name'],
aggregate_row['signature'], aggregate_row['state_func'], state_type,
aggregate_row['final_func'], initial_condition, return_type)
def _build_table_metadata(self, row, col_rows=None, trigger_rows=None):
keyspace_name = row["keyspace_name"]
cfname = row[self._table_name_col]
col_rows = col_rows or self.keyspace_table_col_rows[keyspace_name][cfname]
trigger_rows = trigger_rows or self.keyspace_table_trigger_rows[keyspace_name][cfname]
if not col_rows: # CASSANDRA-8487
log.warning("Building table metadata with no column meta for %s.%s",
keyspace_name, cfname)
table_meta = TableMetadata(keyspace_name, cfname)
try:
comparator = types.lookup_casstype(row["comparator"])
table_meta.comparator = comparator
if issubclass(comparator, types.CompositeType):
column_name_types = comparator.subtypes
is_composite_comparator = True
else:
column_name_types = (comparator,)
is_composite_comparator = False
num_column_name_components = len(column_name_types)
last_col = column_name_types[-1]
column_aliases = row.get("column_aliases", None)
clustering_rows = [r for r in col_rows
if r.get('type', None) == "clustering_key"]
if len(clustering_rows) > 1:
clustering_rows = sorted(clustering_rows, key=lambda row: row.get('component_index'))
if column_aliases is not None:
column_aliases = json.loads(column_aliases)
else:
column_aliases = [r.get('column_name') for r in clustering_rows]
if is_composite_comparator:
if issubclass(last_col, types.ColumnToCollectionType):
# collections
is_compact = False
has_value = False
clustering_size = num_column_name_components - 2
elif (len(column_aliases) == num_column_name_components - 1
and issubclass(last_col, types.UTF8Type)):
# aliases?
is_compact = False
has_value = False
clustering_size = num_column_name_components - 1
else:
# compact table
is_compact = True
has_value = column_aliases or not col_rows
clustering_size = num_column_name_components
# Some thrift tables define names in composite types (see PYTHON-192)
if not column_aliases and hasattr(comparator, 'fieldnames'):
column_aliases = comparator.fieldnames
else:
is_compact = True
if column_aliases or not col_rows:
has_value = True
clustering_size = num_column_name_components
else:
has_value = False
clustering_size = 0
# partition key
partition_rows = [r for r in col_rows
if r.get('type', None) == "partition_key"]
if len(partition_rows) > 1:
partition_rows = sorted(partition_rows, key=lambda row: row.get('component_index'))
key_aliases = row.get("key_aliases")
if key_aliases is not None:
key_aliases = json.loads(key_aliases) if key_aliases else []
else:
# In 2.0+, we can use the 'type' column. In 3.0+, we have to use it.
key_aliases = [r.get('column_name') for r in partition_rows]
key_validator = row.get("key_validator")
if key_validator is not None:
key_type = types.lookup_casstype(key_validator)
key_types = key_type.subtypes if issubclass(key_type, types.CompositeType) else [key_type]
else:
key_types = [types.lookup_casstype(r.get('validator')) for r in partition_rows]
for i, col_type in enumerate(key_types):
if len(key_aliases) > i:
column_name = key_aliases[i]
elif i == 0:
column_name = "key"
else:
column_name = "key%d" % i
col = ColumnMetadata(table_meta, column_name, col_type.cql_parameterized_type())
table_meta.columns[column_name] = col
table_meta.partition_key.append(col)
# clustering key
for i in range(clustering_size):
if len(column_aliases) > i:
column_name = column_aliases[i]
else:
column_name = "column%d" % i
data_type = column_name_types[i]
cql_type = _cql_from_cass_type(data_type)
is_reversed = types.is_reversed_casstype(data_type)
col = ColumnMetadata(table_meta, column_name, cql_type, is_reversed=is_reversed)
table_meta.columns[column_name] = col
table_meta.clustering_key.append(col)
# value alias (if present)
if has_value:
value_alias_rows = [r for r in col_rows
if r.get('type', None) == "compact_value"]
if not key_aliases: # TODO are we checking the right thing here?
value_alias = "value"
else:
value_alias = row.get("value_alias", None)
if value_alias is None and value_alias_rows: # CASSANDRA-8487
# In 2.0+, we can use the 'type' column. In 3.0+, we have to use it.
value_alias = value_alias_rows[0].get('column_name')
default_validator = row.get("default_validator")
if default_validator:
validator = types.lookup_casstype(default_validator)
else:
if value_alias_rows: # CASSANDRA-8487
validator = types.lookup_casstype(value_alias_rows[0].get('validator'))
cql_type = _cql_from_cass_type(validator)
col = ColumnMetadata(table_meta, value_alias, cql_type)
if value_alias: # CASSANDRA-8487
table_meta.columns[value_alias] = col
# other normal columns
for col_row in col_rows:
column_meta = self._build_column_metadata(table_meta, col_row)
if column_meta.name:
table_meta.columns[column_meta.name] = column_meta
index_meta = self._build_index_metadata(column_meta, col_row)
if index_meta:
table_meta.indexes[index_meta.name] = index_meta
for trigger_row in trigger_rows:
trigger_meta = self._build_trigger_metadata(table_meta, trigger_row)
table_meta.triggers[trigger_meta.name] = trigger_meta
table_meta.options = self._build_table_options(row)
table_meta.is_compact_storage = is_compact
except Exception:
table_meta._exc_info = sys.exc_info()
log.exception("Error while parsing metadata for table %s.%s row(%s) columns(%s)", keyspace_name, cfname, row, col_rows)
return table_meta
def _build_table_options(self, row):
""" Setup the mostly-non-schema table options, like caching settings """
options = dict((o, row.get(o)) for o in self.recognized_table_options if o in row)
# the option name when creating tables is "dclocal_read_repair_chance",
# but the column name in system.schema_columnfamilies is
# "local_read_repair_chance". We'll store this as dclocal_read_repair_chance,
# since that's probably what users are expecting (and we need it for the
# CREATE TABLE statement anyway).
if "local_read_repair_chance" in options:
val = options.pop("local_read_repair_chance")
options["dclocal_read_repair_chance"] = val
return options
@classmethod
def _build_column_metadata(cls, table_metadata, row):
name = row["column_name"]
type_string = row["validator"]
data_type = types.lookup_casstype(type_string)
cql_type = _cql_from_cass_type(data_type)
is_static = row.get("type", None) == "static"
is_reversed = types.is_reversed_casstype(data_type)
column_meta = ColumnMetadata(table_metadata, name, cql_type, is_static, is_reversed)
column_meta._cass_type = data_type
return column_meta
@staticmethod
def _build_index_metadata(column_metadata, row):
index_name = row.get("index_name")
kind = row.get("index_type")
if index_name or kind:
options = row.get("index_options")
options = json.loads(options) if options else {}
options = options or {} # if the json parsed to None, init empty dict
# generate a CQL index identity string
target = protect_name(column_metadata.name)
if kind != "CUSTOM":
if "index_keys" in options:
target = 'keys(%s)' % (target,)
elif "index_values" in options:
# don't use any "function" for collection values
pass
else:
# it might be a "full" index on a frozen collection, but
# we need to check the data type to verify that, because
# there is no special index option for full-collection
# indexes.
data_type = column_metadata._cass_type
collection_types = ('map', 'set', 'list')
if data_type.typename == "frozen" and data_type.subtypes[0].typename in collection_types:
# no index option for full-collection index
target = 'full(%s)' % (target,)
options['target'] = target
return IndexMetadata(column_metadata.table.keyspace_name, column_metadata.table.name, index_name, kind, options)
@staticmethod
def _build_trigger_metadata(table_metadata, row):
name = row["trigger_name"]
options = row["trigger_options"]
trigger_meta = TriggerMetadata(table_metadata, name, options)
return trigger_meta
def _query_all(self):
cl = ConsistencyLevel.ONE
queries = [
QueryMessage(query=self._SELECT_KEYSPACES, consistency_level=cl),
QueryMessage(query=self._SELECT_COLUMN_FAMILIES, consistency_level=cl),
QueryMessage(query=self._SELECT_COLUMNS, consistency_level=cl),
QueryMessage(query=self._SELECT_TYPES, consistency_level=cl),
QueryMessage(query=self._SELECT_FUNCTIONS, consistency_level=cl),
QueryMessage(query=self._SELECT_AGGREGATES, consistency_level=cl),
QueryMessage(query=self._SELECT_TRIGGERS, consistency_level=cl)
]
responses = self.connection.wait_for_responses(*queries, timeout=self.timeout, fail_on_error=False)
(ks_success, ks_result), (table_success, table_result), \
(col_success, col_result), (types_success, types_result), \
(functions_success, functions_result), \
(aggregates_success, aggregates_result), \
(triggers_success, triggers_result) = responses
self.keyspaces_result = self._handle_results(ks_success, ks_result)
self.tables_result = self._handle_results(table_success, table_result)
self.columns_result = self._handle_results(col_success, col_result)
# if we're connected to Cassandra < 2.0, the triggers table will not exist
if triggers_success:
self.triggers_result = dict_factory(*triggers_result.results)
else:
if isinstance(triggers_result, InvalidRequest):
log.debug("triggers table not found")
elif isinstance(triggers_result, Unauthorized):
log.warning("this version of Cassandra does not allow access to schema_triggers metadata with authorization enabled (CASSANDRA-7967); "
"The driver will operate normally, but will not reflect triggers in the local metadata model, or schema strings.")
else:
raise triggers_result
# if we're connected to Cassandra < 2.1, the usertypes table will not exist
if types_success:
self.types_result = dict_factory(*types_result.results)
else:
if isinstance(types_result, InvalidRequest):
log.debug("user types table not found")
self.types_result = {}
else:
raise types_result
# functions were introduced in Cassandra 2.2
if functions_success:
self.functions_result = dict_factory(*functions_result.results)
else:
if isinstance(functions_result, InvalidRequest):
log.debug("user functions table not found")
else:
raise functions_result
# aggregates were introduced in Cassandra 2.2
if aggregates_success:
self.aggregates_result = dict_factory(*aggregates_result.results)
else:
if isinstance(aggregates_result, InvalidRequest):
log.debug("user aggregates table not found")
else:
raise aggregates_result
self._aggregate_results()
def _aggregate_results(self):
m = self.keyspace_table_rows
for row in self.tables_result:
m[row["keyspace_name"]].append(row)
m = self.keyspace_table_col_rows
for row in self.columns_result:
ksname = row["keyspace_name"]
cfname = row[self._table_name_col]
m[ksname][cfname].append(row)
m = self.keyspace_type_rows
for row in self.types_result:
m[row["keyspace_name"]].append(row)
m = self.keyspace_func_rows
for row in self.functions_result:
m[row["keyspace_name"]].append(row)
m = self.keyspace_agg_rows
for row in self.aggregates_result:
m[row["keyspace_name"]].append(row)
m = self.keyspace_table_trigger_rows
for row in self.triggers_result:
ksname = row["keyspace_name"]
cfname = row[self._table_name_col]
m[ksname][cfname].append(row)
@staticmethod
def _schema_type_to_cql(type_string):
cass_type = types.lookup_casstype(type_string)
return _cql_from_cass_type(cass_type)
class SchemaParserV3(SchemaParserV22):
_SELECT_KEYSPACES = "SELECT * FROM system_schema.keyspaces"
_SELECT_TABLES = "SELECT * FROM system_schema.tables"
_SELECT_COLUMNS = "SELECT * FROM system_schema.columns"
_SELECT_INDEXES = "SELECT * FROM system_schema.indexes"
_SELECT_TRIGGERS = "SELECT * FROM system_schema.triggers"
_SELECT_TYPES = "SELECT * FROM system_schema.types"
_SELECT_FUNCTIONS = "SELECT * FROM system_schema.functions"
_SELECT_AGGREGATES = "SELECT * FROM system_schema.aggregates"
_SELECT_VIEWS = "SELECT * FROM system_schema.views"
_table_name_col = 'table_name'
_function_agg_arument_type_col = 'argument_types'
recognized_table_options = (
'bloom_filter_fp_chance',
'caching',
'comment',
'compaction',
'compression',
'crc_check_chance',
'dclocal_read_repair_chance',
'default_time_to_live',
'gc_grace_seconds',
'max_index_interval',
'memtable_flush_period_in_ms',
'min_index_interval',
'read_repair_chance',
'speculative_retry')
def __init__(self, connection, timeout):
super(SchemaParserV3, self).__init__(connection, timeout)
self.indexes_result = []
self.keyspace_table_index_rows = defaultdict(lambda: defaultdict(list))
self.keyspace_view_rows = defaultdict(list)
def get_all_keyspaces(self):
for keyspace_meta in super(SchemaParserV3, self).get_all_keyspaces():
for row in self.keyspace_view_rows[keyspace_meta.name]:
view_meta = self._build_view_metadata(row)
keyspace_meta._add_view_metadata(view_meta)
yield keyspace_meta
def get_table(self, keyspaces, keyspace, table):
cl = ConsistencyLevel.ONE
where_clause = bind_params(" WHERE keyspace_name = %%s AND %s = %%s" % (self._table_name_col), (keyspace, table), _encoder)
cf_query = QueryMessage(query=self._SELECT_TABLES + where_clause, consistency_level=cl)
col_query = QueryMessage(query=self._SELECT_COLUMNS + where_clause, consistency_level=cl)
indexes_query = QueryMessage(query=self._SELECT_INDEXES + where_clause, consistency_level=cl)
triggers_query = QueryMessage(query=self._SELECT_TRIGGERS + where_clause, consistency_level=cl)
# in protocol v4 we don't know if this event is a view or a table, so we look for both
where_clause = bind_params(" WHERE keyspace_name = %s AND view_name = %s", (keyspace, table), _encoder)
view_query = QueryMessage(query=self._SELECT_VIEWS + where_clause,
consistency_level=cl)
(cf_success, cf_result), (col_success, col_result), (indexes_sucess, indexes_result), \
(triggers_success, triggers_result), (view_success, view_result) \
= self.connection.wait_for_responses(cf_query, col_query, indexes_query, triggers_query, view_query,
timeout=self.timeout, fail_on_error=False)
table_result = self._handle_results(cf_success, cf_result)
col_result = self._handle_results(col_success, col_result)
if table_result:
indexes_result = self._handle_results(indexes_sucess, indexes_result)
triggers_result = self._handle_results(triggers_success, triggers_result)
return self._build_table_metadata(table_result[0], col_result, triggers_result, indexes_result)
view_result = self._handle_results(view_success, view_result)
if view_result:
return self._build_view_metadata(view_result[0], col_result)
@staticmethod
def _build_keyspace_metadata_internal(row):
name = row["keyspace_name"]
durable_writes = row["durable_writes"]
strategy_options = dict(row["replication"])
strategy_class = strategy_options.pop("class")
return KeyspaceMetadata(name, durable_writes, strategy_class, strategy_options)
@staticmethod
def _build_aggregate(aggregate_row):
return Aggregate(aggregate_row['keyspace_name'], aggregate_row['aggregate_name'],
aggregate_row['argument_types'], aggregate_row['state_func'], aggregate_row['state_type'],
aggregate_row['final_func'], aggregate_row['initcond'], aggregate_row['return_type'])
def _build_table_metadata(self, row, col_rows=None, trigger_rows=None, index_rows=None):
keyspace_name = row["keyspace_name"]
table_name = row[self._table_name_col]
col_rows = col_rows or self.keyspace_table_col_rows[keyspace_name][table_name]
trigger_rows = trigger_rows or self.keyspace_table_trigger_rows[keyspace_name][table_name]
index_rows = index_rows or self.keyspace_table_index_rows[keyspace_name][table_name]
table_meta = TableMetadataV3(keyspace_name, table_name)
try:
table_meta.options = self._build_table_options(row)
flags = row.get('flags', set())
if flags:
compact_static = False
table_meta.is_compact_storage = 'dense' in flags or 'super' in flags or 'compound' not in flags
is_dense = 'dense' in flags
else:
compact_static = True
table_meta.is_compact_storage = True
is_dense = False
self._build_table_columns(table_meta, col_rows, compact_static, is_dense)
for trigger_row in trigger_rows:
trigger_meta = self._build_trigger_metadata(table_meta, trigger_row)
table_meta.triggers[trigger_meta.name] = trigger_meta
for index_row in index_rows:
index_meta = self._build_index_metadata(table_meta, index_row)
if index_meta:
table_meta.indexes[index_meta.name] = index_meta
except Exception:
table_meta._exc_info = sys.exc_info()
log.exception("Error while parsing metadata for table %s.%s row(%s) columns(%s)", keyspace_name, table_name, row, col_rows)
return table_meta
def _build_table_options(self, row):
""" Setup the mostly-non-schema table options, like caching settings """
return dict((o, row.get(o)) for o in self.recognized_table_options if o in row)
def _build_table_columns(self, meta, col_rows, compact_static=False, is_dense=False):
# partition key
partition_rows = [r for r in col_rows
if r.get('kind', None) == "partition_key"]
if len(partition_rows) > 1:
partition_rows = sorted(partition_rows, key=lambda row: row.get('position'))
for r in partition_rows:
# we have to add meta here (and not in the later loop) because TableMetadata.columns is an
# OrderedDict, and it assumes keys are inserted first, in order, when exporting CQL
column_meta = self._build_column_metadata(meta, r)
meta.columns[column_meta.name] = column_meta
meta.partition_key.append(meta.columns[r.get('column_name')])
# clustering key
if not compact_static:
clustering_rows = [r for r in col_rows
if r.get('kind', None) == "clustering"]
if len(clustering_rows) > 1:
clustering_rows = sorted(clustering_rows, key=lambda row: row.get('position'))
for r in clustering_rows:
column_meta = self._build_column_metadata(meta, r)
meta.columns[column_meta.name] = column_meta
meta.clustering_key.append(meta.columns[r.get('column_name')])
for col_row in (r for r in col_rows
if r.get('kind', None) not in ('partition_key', 'clustering_key')):
column_meta = self._build_column_metadata(meta, col_row)
if is_dense and column_meta.cql_type == types.cql_empty_type:
continue
if compact_static and not column_meta.is_static:
# for compact static tables, we omit the clustering key and value, and only add the logical columns.
# They are marked not static so that it generates appropriate CQL
continue
if compact_static:
column_meta.is_static = False
meta.columns[column_meta.name] = column_meta
def _build_view_metadata(self, row, col_rows=None):
keyspace_name = row["keyspace_name"]
view_name = row["view_name"]
base_table_name = row["base_table_name"]
include_all_columns = row["include_all_columns"]
where_clause = row["where_clause"]
col_rows = col_rows or self.keyspace_table_col_rows[keyspace_name][view_name]
view_meta = MaterializedViewMetadata(keyspace_name, view_name, base_table_name,
include_all_columns, where_clause, self._build_table_options(row))
self._build_table_columns(view_meta, col_rows)
return view_meta
@staticmethod
def _build_column_metadata(table_metadata, row):
name = row["column_name"]
cql_type = row["type"]
is_static = row.get("kind", None) == "static"
is_reversed = row["clustering_order"].upper() == "DESC"
column_meta = ColumnMetadata(table_metadata, name, cql_type, is_static, is_reversed)
return column_meta
@staticmethod
def _build_index_metadata(table_metadata, row):
index_name = row.get("index_name")
kind = row.get("kind")
if index_name or kind:
index_options = row.get("options")
return IndexMetadata(table_metadata.keyspace_name, table_metadata.name, index_name, kind, index_options)
else:
return None
@staticmethod
def _build_trigger_metadata(table_metadata, row):
name = row["trigger_name"]
options = row["options"]
trigger_meta = TriggerMetadata(table_metadata, name, options)
return trigger_meta
def _query_all(self):
cl = ConsistencyLevel.ONE
queries = [
QueryMessage(query=self._SELECT_KEYSPACES, consistency_level=cl),
QueryMessage(query=self._SELECT_TABLES, consistency_level=cl),
QueryMessage(query=self._SELECT_COLUMNS, consistency_level=cl),
QueryMessage(query=self._SELECT_TYPES, consistency_level=cl),
QueryMessage(query=self._SELECT_FUNCTIONS, consistency_level=cl),
QueryMessage(query=self._SELECT_AGGREGATES, consistency_level=cl),
QueryMessage(query=self._SELECT_TRIGGERS, consistency_level=cl),
QueryMessage(query=self._SELECT_INDEXES, consistency_level=cl),
QueryMessage(query=self._SELECT_VIEWS, consistency_level=cl)
]
responses = self.connection.wait_for_responses(*queries, timeout=self.timeout, fail_on_error=False)
(ks_success, ks_result), (table_success, table_result), \
(col_success, col_result), (types_success, types_result), \
(functions_success, functions_result), \
(aggregates_success, aggregates_result), \
(triggers_success, triggers_result), \
(indexes_success, indexes_result), \
(views_success, views_result) = responses
self.keyspaces_result = self._handle_results(ks_success, ks_result)
self.tables_result = self._handle_results(table_success, table_result)
self.columns_result = self._handle_results(col_success, col_result)
self.triggers_result = self._handle_results(triggers_success, triggers_result)
self.types_result = self._handle_results(types_success, types_result)
self.functions_result = self._handle_results(functions_success, functions_result)
self.aggregates_result = self._handle_results(aggregates_success, aggregates_result)
self.indexes_result = self._handle_results(indexes_success, indexes_result)
self.views_result = self._handle_results(views_success, views_result)
self._aggregate_results()
def _aggregate_results(self):
super(SchemaParserV3, self)._aggregate_results()
m = self.keyspace_table_index_rows
for row in self.indexes_result:
ksname = row["keyspace_name"]
cfname = row[self._table_name_col]
m[ksname][cfname].append(row)
m = self.keyspace_view_rows
for row in self.views_result:
m[row["keyspace_name"]].append(row)
@staticmethod
def _schema_type_to_cql(type_string):
return type_string
class TableMetadataV3(TableMetadata):
compaction_options = {}
option_maps = ['compaction', 'compression', 'caching']
@property
def is_cql_compatible(self):
return True
@classmethod
def _make_option_strings(cls, options_map):
ret = []
options_copy = dict(options_map.items())
for option in cls.option_maps:
value = options_copy.get(option)
if isinstance(value, Mapping):
del options_copy[option]
params = ("'%s': '%s'" % (k, v) for k, v in value.items())
ret.append("%s = {%s}" % (option, ', '.join(params)))
for name, value in options_copy.items():
if value is not None:
if name == "comment":
value = value or ""
ret.append("%s = %s" % (name, protect_value(value)))
return list(sorted(ret))
def get_schema_parser(connection, timeout):
server_version = connection.server_version
if server_version.startswith('3'):
return SchemaParserV3(connection, timeout)
else:
# we could further specialize by version. Right now just refactoring the
# multi-version parser we have as of C* 2.2.0rc1.
return SchemaParserV22(connection, timeout)
def _cql_from_cass_type(cass_type):
"""
A string representation of the type for this column, such as "varchar"
or "map<string, int>".
"""
if issubclass(cass_type, types.ReversedType):
return cass_type.subtypes[0].cql_parameterized_type()
else:
return cass_type.cql_parameterized_type()