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# This file is part of daf_butler. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (http://www.lsst.org). 

# See the COPYRIGHT file at the top-level directory of this distribution 

# for details of code ownership. 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the GNU General Public License 

# along with this program. If not, see <http://www.gnu.org/licenses/>. 

 

"""Chained datastore.""" 

 

import time 

import logging 

import os 

import warnings 

 

from lsst.utils import doImport 

from lsst.daf.butler import Datastore, DatastoreConfig, StorageClassFactory, DatasetTypeNotSupportedError 

 

log = logging.getLogger(__name__) 

 

__all__ = ("ChainedDatastore", ) 

 

 

class ChainedDatastore(Datastore): 

"""Chained Datastores to allow read and writes from multiple datastores. 

 

A ChainedDatastore is configured with multiple datastore configurations. 

A ``put()`` is always sent to each datastore. A ``get()`` 

operation is sent to each datastore in turn and the first datastore 

to return a valid dataset is used. 

 

Attributes 

---------- 

config : `DatastoreConfig` 

Configuration used to create Datastore. 

storageClassFactory : `StorageClassFactory` 

Factory for creating storage class instances from name. 

name : `str` 

Label associated with this Datastore. 

 

Parameters 

---------- 

config : `DatastoreConfig` or `str` 

Configuration. This configuration must include a ``datastores`` field 

as a sequence of datastore configurations. The order in this sequence 

indicates the order to use for read operations. 

""" 

 

defaultConfigFile = "datastores/chainedDatastore.yaml" 

"""Path to configuration defaults. Relative to $DAF_BUTLER_DIR/config or 

absolute path. Can be None if no defaults specified. 

""" 

 

containerKey = "datastores" 

"""Key to specify where child datastores are configured.""" 

 

@classmethod 

def setConfigRoot(cls, root, config, full): 

"""Set any filesystem-dependent config options for child Datastores to 

be appropriate for a new empty repository with the given root. 

 

Parameters 

---------- 

root : `str` 

Filesystem path to the root of the data repository. 

config : `Config` 

A `Config` to update. Only the subset understood by 

this component will be updated. Will not expand 

defaults. 

full : `Config` 

A complete config with all defaults expanded that can be 

converted to a `DatastoreConfig`. Read-only and will not be 

modified by this method. 

Repository-specific options that should not be obtained 

from defaults when Butler instances are constructed 

should be copied from `full` to `Config`. 

""" 

 

# Extract the part of the config we care about updating 

datastoreConfig = DatastoreConfig(config, mergeDefaults=False) 

 

# And the subset of the full config that we can use for reference. 

# Do not bother with defaults because we are told this already has 

# them. 

fullDatastoreConfig = DatastoreConfig(full, mergeDefaults=False) 

 

# Loop over each datastore config and pass the subsets to the 

# child datastores to process. 

 

containerKey = cls.containerKey 

for idx, (child, fullChild) in enumerate(zip(datastoreConfig[containerKey], 

fullDatastoreConfig[containerKey])): 

childConfig = DatastoreConfig(child, mergeDefaults=False) 

fullChildConfig = DatastoreConfig(fullChild, mergeDefaults=False) 

datastoreClass = doImport(fullChildConfig["cls"]) 

newroot = "{}/{}_{}".format(root, datastoreClass.__qualname__, idx) 

datastoreClass.setConfigRoot(newroot, childConfig, fullChildConfig) 

 

# Reattach to parent 

datastoreConfig[containerKey, idx] = childConfig 

 

# Reattach modified datastore config to parent 

# If this has a datastore key we attach there, otherwise we assume 

# this information goes at the top of the config hierarchy. 

if DatastoreConfig.component in config: 

config[DatastoreConfig.component] = datastoreConfig 

else: 

config.update(datastoreConfig) 

 

return 

 

def __init__(self, config, registry=None): 

super().__init__(config, registry) 

 

self.storageClassFactory = StorageClassFactory() 

 

# Scan for child datastores and instantiate them with the same registry 

self.datastores = [] 

for c in self.config["datastores"]: 

c = DatastoreConfig(c) 

datastoreType = doImport(c["cls"]) 

datastore = datastoreType(c, registry) 

log.debug("Creating child datastore %s", datastore.name) 

self.datastores.append(datastore) 

 

# Name ourself based on our children 

140 ↛ 143line 140 didn't jump to line 143, because the condition on line 140 was never false if self.datastores: 

childNames = ",".join([d.name for d in self.datastores]) 

else: 

childNames = "(empty@{})".format(time.time()) 

self.name = "{}[{}]".format(type(self).__qualname__, childNames) 

 

# We declare we are ephemeral if all our child datastores declare 

# they are ephemeral 

isEphemeral = True 

for d in self.datastores: 

if not d.isEphemeral: 

isEphemeral = False 

break 

self.isEphemeral = isEphemeral 

 

log.debug("Created %s (%s)", self.name, ("ephemeral" if self.isEphemeral else "permanent")) 

 

def __str__(self): 

chainName = ", ".join(str(ds) for ds in self.datastores) 

return chainName 

 

def exists(self, ref): 

"""Check if the dataset exists in one of the datastores. 

 

Parameters 

---------- 

ref : `DatasetRef` 

Reference to the required dataset. 

 

Returns 

------- 

exists : `bool` 

`True` if the entity exists in one of the child datastores. 

""" 

for datastore in self.datastores: 

if datastore.exists(ref): 

log.debug("Found %s in datastore %s", ref, datastore.name) 

return True 

return False 

 

def get(self, ref, parameters=None): 

"""Load an InMemoryDataset from the store. 

 

The dataset is returned from the first datastore that has 

the dataset. 

 

Parameters 

---------- 

ref : `DatasetRef` 

Reference to the required Dataset. 

parameters : `dict` 

`StorageClass`-specific parameters that specify, for example, 

a slice of the Dataset to be loaded. 

 

Returns 

------- 

inMemoryDataset : `object` 

Requested Dataset or slice thereof as an InMemoryDataset. 

 

Raises 

------ 

FileNotFoundError 

Requested dataset can not be retrieved. 

TypeError 

Return value from formatter has unexpected type. 

ValueError 

Formatter failed to process the dataset. 

""" 

 

for datastore in self.datastores: 

try: 

inMemoryObject = datastore.get(ref, parameters) 

log.debug("Found Dataset %s in datastore %s", ref, datastore.name) 

return inMemoryObject 

except FileNotFoundError: 

pass 

 

raise FileNotFoundError("Dataset {} could not be found in any of the datastores".format(ref)) 

 

def put(self, inMemoryDataset, ref): 

"""Write a InMemoryDataset with a given `DatasetRef` to each 

datastore. 

 

The put() to child datastores can fail with 

`DatasetTypeNotSupportedError`. The put() for this datastore will be 

deemed to have succeeded so long as at least one child datastore 

accepted the inMemoryDataset. 

 

Parameters 

---------- 

inMemoryDataset : `object` 

The Dataset to store. 

ref : `DatasetRef` 

Reference to the associated Dataset. 

 

Raises 

------ 

TypeError 

Supplied object and storage class are inconsistent. 

DatasetTypeNotSupportedError 

All datastores reported `DatasetTypeNotSupportedError`. 

""" 

log.debug("Put %s", ref) 

 

isPermanent = False 

nsuccess = 0 

npermanent = 0 

nephemeral = 0 

for datastore in self.datastores: 

if datastore.isEphemeral: 

nephemeral += 1 

else: 

npermanent += 1 

try: 

datastore.put(inMemoryDataset, ref) 

nsuccess += 1 

if not datastore.isEphemeral: 

isPermanent = True 

except DatasetTypeNotSupportedError: 

pass 

 

261 ↛ 262line 261 didn't jump to line 262, because the condition on line 261 was never true if nsuccess == 0: 

raise DatasetTypeNotSupportedError(f"None of the chained datastores supported ref {ref}") 

 

264 ↛ 265line 264 didn't jump to line 265, because the condition on line 264 was never true if not isPermanent and npermanent > 0: 

warnings.warn(f"Put of {ref} only succeeded in ephemeral databases", stacklevel=2) 

 

if self._transaction is not None: 

self._transaction.registerUndo('put', self.remove, ref) 

 

def ingest(self, path, ref, formatter=None, transfer=None): 

"""Add an on-disk file with the given `DatasetRef` to the store, 

possibly transferring it. 

 

This method is forwarded to each of the chained datastores, trapping 

cases where a datastore has not implemented file ingest and ignoring 

them. 

 

Notes 

----- 

If an absolute path is given and "move" mode is specified, then 

we tell the child datastore to use "copy" mode and unlink it 

at the end. If a relative path is given then it is assumed the file 

is already inside the child datastore. 

 

A transfer mode of None implies that the file is already within 

each of the (relevant) child datastores. 

 

Parameters 

---------- 

path : `str` 

File path. Treated as relative to the repository root of each 

child datastore if not absolute. 

ref : `DatasetRef` 

Reference to the associated Dataset. 

formatter : `Formatter` (optional) 

Formatter that should be used to retreive the Dataset. If not 

provided, the formatter will be constructed according to 

Datastore configuration. 

transfer : str (optional) 

If not None, must be one of 'move', 'copy', 'hardlink', or 

'symlink' indicating how to transfer the file. The new 

filename and location will be determined via template substitution, 

as with ``put``. If the file is outside the datastore root, it 

must be transferred somehow. 

 

Raises 

------ 

NotImplementedError 

If all chained datastores have no ingest implemented or if 

a transfer mode of `None` is specified. 

""" 

log.debug("Ingesting %s (transfer=%s)", ref, transfer) 

 

if transfer is None: 

raise NotImplementedError("ChainedDatastore does not support transfer=None") 

 

# A "move" is sometimes a "copy" 

moveIsCopy = False 

if transfer == "move" and os.path.isabs(path): 

moveIsCopy = True 

 

counter = 0 

for datastore in self.datastores: 

dstransfer = transfer 

# Each child datastore must copy the file for a move operation 

if moveIsCopy: 

dstransfer = "copy" 

try: 

datastore.ingest(path, ref, transfer=dstransfer, formatter=formatter) 

except NotImplementedError: 

counter += 1 

 

if counter == len(self.datastores): 

raise NotImplementedError("Ingest not implemented by any of the chained datastores") 

 

# if the file was meant to be moved then we have to delete it 

if moveIsCopy: 

os.unlink(path) 

 

def getUri(self, ref, predict=False): 

"""URI to the Dataset. 

 

The returned URI is from the first datastore in the list that has 

the dataset with preference given to the first dataset coming from 

a permanent datastore. If no datastores have the dataset and prediction 

is allowed, the predicted URI for the first datastore in the list will 

be returned. 

 

Parameters 

---------- 

ref : `DatasetRef` 

Reference to the required Dataset. 

predict : `bool` 

If `True`, allow URIs to be returned of datasets that have not 

been written. 

 

Returns 

------- 

uri : `str` 

URI string pointing to the Dataset within the datastore. If the 

Dataset does not exist in the datastore, and if ``predict`` is 

`True`, the URI will be a prediction and will include a URI 

fragment "#predicted". 

 

Notes 

----- 

If the datastore does not have entities that relate well 

to the concept of a URI the returned URI string will be 

descriptive. The returned URI is not guaranteed to be obtainable. 

 

Raises 

------ 

FileNotFoundError 

A URI has been requested for a dataset that does not exist and 

guessing is not allowed. 

""" 

log.debug("Requesting URI for %s", ref) 

predictedUri = None 

predictedEphemeralUri = None 

firstEphemeralUri = None 

for datastore in self.datastores: 

if datastore.exists(ref): 

if not datastore.isEphemeral: 

uri = datastore.getUri(ref) 

log.debug("Retrieved ephemeral URI: %s", uri) 

return uri 

elif firstEphemeralUri is None: 

firstEphemeralUri = datastore.getUri(ref) 

elif predict: 

if predictedUri is None and not datastore.isEphemeral: 

predictedUri = datastore.getUri(ref, predict) 

elif predictedEphemeralUri is None and datastore.isEphemeral: 

predictedEphemeralUri = datastore.getUri(ref, predict) 

 

if firstEphemeralUri is not None: 

log.debug("Retrieved ephemeral URI: %s", firstEphemeralUri) 

return firstEphemeralUri 

 

if predictedUri is not None: 

log.debug("Retrieved predicted URI: %s", predictedUri) 

return predictedUri 

 

if predictedEphemeralUri is not None: 

log.debug("Retrieved predicted ephemeral URI: %s", predictedEphemeralUri) 

return predictedEphemeralUri 

 

raise FileNotFoundError("Dataset {} not in any datastore".format(ref)) 

 

def remove(self, ref): 

"""Indicate to the Datastore that a Dataset can be removed. 

 

The dataset will be removed from each datastore. The dataset is 

not required to exist in every child datastore. 

 

Parameters 

---------- 

ref : `DatasetRef` 

Reference to the required Dataset. 

 

Raises 

------ 

FileNotFoundError 

Attempt to remove a dataset that does not exist. Raised if none 

of the child datastores removed the dataset. 

""" 

log.debug(f"Removing {ref}") 

 

counter = 0 

for datastore in self.datastores: 

try: 

datastore.remove(ref) 

counter += 1 

except FileNotFoundError: 

pass 

 

if counter == 0: 

raise FileNotFoundError(f"Could not remove from any child datastore: {ref}") 

 

def transfer(self, inputDatastore, ref): 

"""Retrieve a Dataset from an input `Datastore`, 

and store the result in this `Datastore`. 

 

Parameters 

---------- 

inputDatastore : `Datastore` 

The external `Datastore` from which to retreive the Dataset. 

ref : `DatasetRef` 

Reference to the required Dataset in the input data store. 

 

Returns 

------- 

results : `list` 

List containing the return value from the ``put()`` to each 

child datastore. 

""" 

assert inputDatastore is not self # unless we want it for renames? 

inMemoryDataset = inputDatastore.get(ref) 

return [datastore.put(inMemoryDataset, ref) for datastore in self.datastores]