def pre_index(new_index, old_index, alias, indexer, settings):
"""
This sets up everything needed before indexing:
* Flags the database.
* Creates the new index.
"""
# Flag the database to indicate that the reindexing has started.
_print('Flagging the database to start the reindexation.', alias)
Reindexing.flag_reindexing(new_index=new_index,
old_index=old_index,
alias=alias)
time.sleep(5) # Give celeryd some time to flag the DB.
_print('Creating the mapping for index {index}.'.format(index=new_index),
alias)
# Update settings with mapping.
settings = {
'settings': settings,
'mappings': indexer.get_mapping(),
}
# Create index and mapping.
try:
ES.indices.create(index=new_index, body=settings)
except elasticsearch.ElasticsearchException as e:
raise CommandError('ERROR: New index [%s] already exists? %s' %
(new_index, e))
# Don't return until the health is green. By default waits for 30s.
ES.cluster.health(index=new_index,
wait_for_status='green',
wait_for_relocating_shards=0)
def pre_index(new_index, old_index, alias, index_name, settings):
"""
This sets up everything needed before indexing:
* Flags the database.
* Creates the new index.
"""
indexer = INDEXER_MAP[index_name]
# Flag the database to indicate that the reindexing has started.
_print('Flagging the database to start the reindexation.', alias)
Reindexing.flag_reindexing(new_index=new_index, old_index=old_index,
alias=alias)
time.sleep(5) # Give the celery worker some time to flag the DB.
_print('Creating the mapping for index {index}.'.format(index=new_index),
alias)
# Update settings with mapping.
settings = {
'settings': settings,
'mappings': indexer.get_mapping(),
}
# Create index and mapping.
try:
ES.indices.create(index=new_index, body=settings)
except elasticsearch.ElasticsearchException as e:
raise CommandError('ERROR: New index [%s] already exists? %s'
% (new_index, e))
# Don't return until the health is green. By default waits for 30s.
ES.cluster.health(index=new_index, wait_for_status='green',
wait_for_relocating_shards=0)
def test_get_indices(self):
# Not reindexing.
assert not Reindexing.objects.filter(alias='foo').exists()
assert Reindexing.get_indices('foo') == ['foo']
# Reindexing on 'foo'.
Reindexing.objects.create(alias='foo', new_index='bar',
old_index='baz')
self.assertSetEqual(Reindexing.get_indices('foo'), ['bar', 'baz'])
# Doesn't clash on other aliases.
self.assertSetEqual(Reindexing.get_indices('other'), ['other'])
def test_flag_reindexing(self):
assert Reindexing.objects.count() == 0
# Flagging for the first time.
res = Reindexing.flag_reindexing('foo', 'bar', 'baz')
eq_(Reindexing.objects.filter(alias='foo').count(), 1)
eq_(res.alias, 'foo')
eq_(res.old_index, 'bar')
eq_(res.new_index, 'baz')
# Flagging for the second time.
res = Reindexing.flag_reindexing('foo', 'bar', 'baz')
assert Reindexing.objects.filter(alias='foo').count() == 1
assert res is None
def unindexer(cls, ids=None, _all=False, index=None):
"""
Empties an index, but doesn't delete it. Useful for tearDowns.
ids -- list of IDs to unindex.
_all -- unindex all objects.
"""
if _all:
# Mostly used for test tearDowns.
qs = cls.get_model()
if hasattr(qs, 'with_deleted'):
qs = qs.with_deleted
else:
qs = qs.objects
ids = list(qs.order_by('id').values_list('id', flat=True))
if not ids:
return
log.info('Unindexing %s %s-%s. [%s]' %
(cls.get_model()._meta.model_name, ids[0], ids[-1], len(ids)))
index = index or cls.get_index()
# Note: If reindexing is currently occurring, `get_indices` will return
# more than one index.
indices = Reindexing.get_indices(index)
es = cls.get_es(urls=settings.ES_URLS)
for id_ in ids:
for idx in indices:
try:
cls.unindex(id_=id_, es=es, index=idx)
except elasticsearch.exceptions.NotFoundError:
# Ignore if it's not there.
log.info(u'[%s:%s] object not found in index' %
(cls.get_model()._meta.model_name, id_))
def post_index(new_index, old_index, alias, index_name, settings):
"""
Perform post-indexing tasks:
* Optimize (which also does a refresh and a flush by default).
* Update settings to reset number of replicas.
* Point the alias to this new index.
* Unflag the database.
* Remove the old index.
* Output the current alias configuration.
"""
_print('Optimizing, updating settings and aliases.', alias)
# Optimize.
ES.indices.optimize(index=new_index)
# Update the replicas.
ES.indices.put_settings(index=new_index, body=settings)
# Add and remove aliases.
actions = [
{'add': {'index': new_index, 'alias': alias}}
]
if old_index:
actions.append(
{'remove': {'index': old_index, 'alias': alias}}
)
ES.indices.update_aliases(body=dict(actions=actions))
_print('Unflagging the database.', alias)
Reindexing.unflag_reindexing(alias=alias)
_print('Removing index {index}.'.format(index=old_index), alias)
if old_index and ES.indices.exists(index=old_index):
ES.indices.delete(index=old_index)
alias_output = ''
for indexer in INDEXERS:
alias = ES_INDEXES[indexer.get_mapping_type_name()]
alias_output += unicode(ES.indices.get_aliases(index=alias)) + '\n'
_print('Reindexation done. Current aliases configuration: '
'{output}\n'.format(output=alias_output), alias)
def post_index(new_index, old_index, alias, index_name, settings):
"""
Perform post-indexing tasks:
* Optimize (which also does a refresh and a flush by default).
* Update settings to reset number of replicas.
* Point the alias to this new index.
* Unflag the database.
* Remove the old index.
* Output the current alias configuration.
"""
_print('Optimizing, updating settings and aliases.', alias)
# Optimize.
ES.indices.optimize(index=new_index)
# Update the replicas.
ES.indices.put_settings(index=new_index, body=settings)
# Add and remove aliases.
actions = [{'add': {'index': new_index, 'alias': alias}}]
if old_index:
actions.append({'remove': {'index': old_index, 'alias': alias}})
ES.indices.update_aliases(body=dict(actions=actions))
_print('Unflagging the database.', alias)
Reindexing.unflag_reindexing(alias=alias)
_print('Removing index {index}.'.format(index=old_index), alias)
if old_index and ES.indices.exists(index=old_index):
ES.indices.delete(index=old_index)
alias_output = ''
for indexer in INDEXERS:
alias = ES_INDEXES[indexer.get_mapping_type_name()]
alias_output += unicode(ES.indices.get_aliases(index=alias)) + '\n'
_print(
'Reindexation done. Current aliases configuration: '
'{output}\n'.format(output=alias_output), alias)
def index(ids, indexer, **kw):
"""
Given a list of IDs and an indexer, index into ES.
If an reindexation is currently occurring, index on both the old and new.
"""
task_log.info("Indexing {0} {1}-{2}. [{3}]".format(indexer.get_model()._meta.model_name, ids[0], ids[-1], len(ids)))
# If reindexing is currently occurring, index on both old and new indexes.
indices = Reindexing.get_indices(indexer.get_index())
es = indexer.get_es(urls=settings.ES_URLS)
for obj in indexer.get_indexable().filter(id__in=ids):
doc = indexer.extract_document(obj.id, obj)
for idx in indices:
indexer.index(doc, id_=obj.id, es=es, index=idx)
def index_webapps(ids, **kw):
"""TODO: use search/indexers.py:index."""
task_log.info('Indexing apps %s-%s. [%s]' % (ids[0], ids[-1], len(ids)))
index = kw.pop('index', WebappIndexer.get_index())
# Note: If reindexing is currently occurring, `get_indices` will return
# more than one index.
indices = Reindexing.get_indices(index)
es = WebappIndexer.get_es(urls=settings.ES_URLS)
qs = Webapp.indexing_transformer(Webapp.with_deleted.no_cache().filter(
id__in=ids))
for obj in qs:
doc = WebappIndexer.extract_document(obj.id, obj)
for idx in indices:
WebappIndexer.index(doc, id_=obj.id, es=es, index=idx)
def index(ids, indexer, **kw):
"""
Given a list of IDs and an indexer, index into ES.
If an reindexation is currently occurring, index on both the old and new.
"""
log.info('Indexing {0} {1}-{2}. [{3}]'.format(
indexer.get_model()._meta.model_name, ids[0], ids[-1], len(ids)))
# If reindexing is currently occurring, index on both old and new indexes.
indices = Reindexing.get_indices(indexer.get_index())
es = indexer.get_es(urls=settings.ES_URLS)
for obj in indexer.get_indexable().filter(id__in=ids):
doc = indexer.extract_document(obj.id, obj)
for idx in indices:
indexer.index(doc, id_=obj.id, es=es, index=idx)
def unindex_webapps(ids, **kw):
if not ids:
return
task_log.info('Un-indexing apps %s-%s. [%s]' % (ids[0], ids[-1], len(ids)))
index = kw.pop('index', WebappIndexer.get_index())
# Note: If reindexing is currently occurring, `get_indices` will return
# more than one index.
indices = Reindexing.get_indices(index)
es = WebappIndexer.get_es(urls=settings.ES_URLS)
for id_ in ids:
for idx in indices:
try:
WebappIndexer.unindex(id_=id_, es=es, index=idx)
except ElasticHttpNotFoundError:
# Ignore if it's not there.
task_log.info(
u'[Webapp:%s] Unindexing app but not found in index' % id_)
def unindexer(cls, ids=None, _all=False, index=None):
"""
Empties an index, but doesn't delete it. Useful for tearDowns.
ids -- list of IDs to unindex.
_all -- unindex all objects.
"""
if _all:
# Mostly used for test tearDowns.
qs = cls.get_model()
if hasattr(qs, 'with_deleted'):
qs = qs.with_deleted
else:
qs = qs.objects
ids = list(qs.order_by('id').values_list('id', flat=True))
if not ids:
return
task_log.info('Unindexing %s %s-%s. [%s]' %
(cls.get_model()._meta.model_name, ids[0], ids[-1],
len(ids)))
index = index or cls.get_index()
# Note: If reindexing is currently occurring, `get_indices` will return
# more than one index.
indices = Reindexing.get_indices(index)
es = cls.get_es(urls=settings.ES_URLS)
for id_ in ids:
for idx in indices:
try:
cls.unindex(id_=id_, es=es, index=idx)
except elasticsearch.exceptions.NotFoundError:
# Ignore if it's not there.
task_log.info(u'[%s:%s] object not found in index' %
(cls.get_model()._meta.model_name, id_))
def test_unflag_reindexing(self):
assert Reindexing.objects.filter(alias='foo').count() == 0
# Unflagging unflagged database does nothing.
Reindexing.unflag_reindexing(alias='foo')
assert Reindexing.objects.filter(alias='foo').count() == 0
# Flag, then unflag.
Reindexing.objects.create(alias='foo', new_index='bar',
old_index='baz')
assert Reindexing.objects.filter(alias='foo').count() == 1
Reindexing.unflag_reindexing(alias='foo')
assert Reindexing.objects.filter(alias='foo').count() == 0
# Unflagging another alias doesn't clash.
Reindexing.objects.create(alias='bar', new_index='bar',
old_index='baz')
Reindexing.unflag_reindexing(alias='foo')
assert Reindexing.objects.filter(alias='bar').count() == 1
def handle(self, *args, **kwargs):
"""Set up reindexing tasks.
Creates a Tasktree that creates a new indexes and indexes all objects,
then points the alias to this new index when finished.
"""
index_choice = kwargs.get('index', None)
prefix = kwargs.get('prefix', '')
force = kwargs.get('force', False)
if index_choice:
# If we only want to reindex a subset of indexes.
INDEXES = INDEX_CHOICES.get(index_choice, None)
if INDEXES is None:
raise CommandError('Incorrect index name specified. '
'Choose one of: %s' %
', '.join(INDEX_CHOICES.keys()))
else:
INDEXES = INDEXERS
if Reindexing.is_reindexing() and not force:
raise CommandError('Indexation already occuring - use --force to '
'bypass')
elif force:
Reindexing.unflag_reindexing()
for INDEXER in INDEXES:
index_name = INDEXER.get_mapping_type_name()
chunk_size = INDEXER.chunk_size
alias = ES_INDEXES[index_name]
chunks, total = chunk_indexing(INDEXER, chunk_size)
if not total:
_print('No items to queue.', alias)
else:
total_chunks = int(ceil(total / float(chunk_size)))
_print(
'Indexing {total} items into {n} chunks of size {size}'.
format(total=total, n=total_chunks,
size=chunk_size), alias)
# Get the old index if it exists.
try:
aliases = ES.indices.get_alias(name=alias).keys()
except elasticsearch.NotFoundError:
aliases = []
old_index = aliases[0] if aliases else None
# Create a new index, using the index name with a timestamp.
new_index = timestamp_index(prefix + alias)
# See how the index is currently configured.
if old_index:
try:
s = (ES.indices.get_settings(index=old_index).get(
old_index, {}).get('settings', {}))
except elasticsearch.NotFoundError:
s = {}
else:
s = {}
num_replicas = s.get('number_of_replicas',
settings.ES_DEFAULT_NUM_REPLICAS)
num_shards = s.get('number_of_shards',
settings.ES_DEFAULT_NUM_SHARDS)
pre_task = pre_index.si(
new_index, old_index, alias, index_name, {
'analysis': INDEXER.get_analysis(),
'number_of_replicas': 0,
'number_of_shards': num_shards,
'store.compress.tv': True,
'store.compress.stored': True,
'refresh_interval': '-1'
})
post_task = post_index.si(new_index, old_index, alias, index_name,
{
'number_of_replicas': num_replicas,
'refresh_interval': '5s'
})
# Ship it.
if not total:
# If there's no data we still create the index and alias.
chain(pre_task, post_task).apply_async()
else:
index_tasks = [
run_indexing.si(new_index, index_name, chunk)
for chunk in chunks
]
if settings.CELERY_ALWAYS_EAGER:
# Eager mode and chords don't get along. So we serialize
# the tasks as a workaround.
index_tasks.insert(0, pre_task)
index_tasks.append(post_task)
chain(*index_tasks).apply_async()
else:
chain(pre_task, chord(header=index_tasks,
body=post_task)).apply_async()
_print('New index and indexing tasks all queued up.')
def handle(self, *args, **kwargs):
"""Set up reindexing tasks.
Creates a Tasktree that creates a new indexes and indexes all objects,
then points the alias to this new index when finished.
"""
index_choice = kwargs.get('index', None)
prefix = kwargs.get('prefix', '')
force = kwargs.get('force', False)
if index_choice:
# If we only want to reindex a subset of indexes.
INDEXES = INDEX_CHOICES.get(index_choice, None)
if INDEXES is None:
raise CommandError(
'Incorrect index name specified. '
'Choose one of: %s' % ', '.join(INDEX_CHOICES.keys()))
else:
INDEXES = INDEXERS
if Reindexing.is_reindexing() and not force:
raise CommandError('Indexation already occuring - use --force to '
'bypass')
elif force:
Reindexing.unflag_reindexing()
for INDEXER in INDEXES:
index_name = INDEXER.get_mapping_type_name()
chunk_size = INDEXER.chunk_size
alias = ES_INDEXES[index_name]
chunks, total = chunk_indexing(INDEXER, chunk_size)
if not total:
_print('No items to queue.', alias)
else:
total_chunks = int(ceil(total / float(chunk_size)))
_print('Indexing {total} items into {n} chunks of size {size}'
.format(total=total, n=total_chunks, size=chunk_size),
alias)
# Get the old index if it exists.
try:
aliases = ES.indices.get_alias(name=alias).keys()
except elasticsearch.NotFoundError:
aliases = []
old_index = aliases[0] if aliases else None
# Create a new index, using the index name with a timestamp.
new_index = timestamp_index(prefix + alias)
# See how the index is currently configured.
if old_index:
try:
s = (ES.indices.get_settings(index=old_index).get(
old_index, {}).get('settings', {}))
except elasticsearch.NotFoundError:
s = {}
else:
s = {}
num_replicas = s.get('number_of_replicas',
settings.ES_DEFAULT_NUM_REPLICAS)
num_shards = s.get('number_of_shards',
settings.ES_DEFAULT_NUM_SHARDS)
pre_task = pre_index.si(new_index, old_index, alias, index_name, {
'analysis': INDEXER.get_analysis(),
'number_of_replicas': 0,
'number_of_shards': num_shards,
'store.compress.tv': True,
'store.compress.stored': True,
'refresh_interval': '-1'})
post_task = post_index.si(new_index, old_index, alias, index_name,
{'number_of_replicas': num_replicas,
'refresh_interval': '5s'})
# Ship it.
if not total:
# If there's no data we still create the index and alias.
chain(pre_task, post_task).apply_async()
else:
index_tasks = [run_indexing.si(new_index, index_name, chunk)
for chunk in chunks]
if settings.CELERY_ALWAYS_EAGER:
# Eager mode and chords don't get along. So we serialize
# the tasks as a workaround.
index_tasks.insert(0, pre_task)
index_tasks.append(post_task)
chain(*index_tasks).apply_async()
else:
chain(pre_task, chord(header=index_tasks,
body=post_task)).apply_async()
_print('New index and indexing tasks all queued up.')
def flag_database(new_index, old_index, alias):
"""Flags the database to indicate that the reindexing has started."""
sys.stdout.write('Flagging the database to start the reindexation\n')
Reindexing.flag_reindexing(new_index=new_index, old_index=old_index,
alias=alias)
time.sleep(5) # Give celeryd some time to flag the DB.
def unflag_database():
"""Unflag the database to indicate that the reindexing is over."""
sys.stdout.write('Unflagging the database\n')
Reindexing.unflag_reindexing()
def test_is_reindexing(self):
assert not Reindexing.is_reindexing()
Reindexing.objects.create(alias='foo', new_index='bar',
old_index='baz')
assert Reindexing.is_reindexing()
def handle(self, *args, **kwargs):
"""Set up reindexing tasks.
Creates a Tasktree that creates a new indexes and indexes all objects,
then points the alias to this new index when finished.
"""
global INDEXES
index_choice = kwargs.get('index', None)
prefix = kwargs.get('prefix', '')
force = kwargs.get('force', False)
if index_choice:
# If we only want to reindex a subset of indexes.
INDEXES = INDEX_DICT.get(index_choice, INDEXES)
if Reindexing.is_reindexing() and not force:
raise CommandError('Indexation already occuring - use --force to '
'bypass')
elif force:
Reindexing.unflag_reindexing()
for ALIAS, INDEXER, CHUNK_SIZE in INDEXES:
chunks, total = chunk_indexing(INDEXER, CHUNK_SIZE)
if not total:
_print('No items to queue.', ALIAS)
else:
total_chunks = int(ceil(total / float(CHUNK_SIZE)))
_print(
'Indexing {total} items into {n} chunks of size {size}'.
format(total=total, n=total_chunks,
size=CHUNK_SIZE), ALIAS)
# Get the old index if it exists.
try:
aliases = ES.indices.get_alias(name=ALIAS).keys()
except elasticsearch.NotFoundError:
aliases = []
old_index = aliases[0] if aliases else None
# Create a new index, using the index name with a timestamp.
new_index = timestamp_index(prefix + ALIAS)
# See how the index is currently configured.
if old_index:
try:
s = (ES.indices.get_settings(index=old_index).get(
old_index, {}).get('settings', {}))
except elasticsearch.NotFoundError:
s = {}
else:
s = {}
num_replicas = s.get('number_of_replicas',
settings.ES_DEFAULT_NUM_REPLICAS)
num_shards = s.get('number_of_shards',
settings.ES_DEFAULT_NUM_SHARDS)
pre_task = pre_index.si(
new_index, old_index, ALIAS, INDEXER, {
'analysis': INDEXER.get_analysis(),
'number_of_replicas': 0,
'number_of_shards': num_shards,
'store.compress.tv': True,
'store.compress.stored': True,
'refresh_interval': '-1'
})
post_task = post_index.si(new_index, old_index, ALIAS, INDEXER, {
'number_of_replicas': num_replicas,
'refresh_interval': '5s'
})
# Ship it.
if not total:
# If there's no data we still create the index and alias.
chain(pre_task, post_task).apply_async()
else:
index_tasks = [
run_indexing.si(new_index, INDEXER, chunk)
for chunk in chunks
]
chain(pre_task, chord(header=index_tasks,
body=post_task)).apply_async()
_print('New index and indexing tasks all queued up.')
def handle(self, *args, **kwargs):
"""Set up reindexing tasks.
Creates a Tasktree that creates a new indexes and indexes all objects,
then points the alias to this new index when finished.
"""
global INDEXES
index_choice = kwargs.get('index', None)
prefix = kwargs.get('prefix', '')
force = kwargs.get('force', False)
if index_choice:
# If we only want to reindex a subset of indexes.
INDEXES = INDEX_DICT.get(index_choice, INDEXES)
if Reindexing.is_reindexing() and not force:
raise CommandError('Indexation already occuring - use --force to '
'bypass')
elif force:
unflag_database()
chain = None
old_indexes = []
for ALIAS, INDEXER, CHUNK_SIZE in INDEXES:
# Get the old index if it exists.
try:
aliases = ES.indices.get_alias(name=ALIAS).keys()
except elasticsearch.NotFoundError:
aliases = []
old_index = aliases[0] if aliases else None
old_indexes.append(old_index)
# Create a new index, using the index name with a timestamp.
new_index = timestamp_index(prefix + ALIAS)
# See how the index is currently configured.
if old_index:
try:
s = (ES.indices.get_settings(index=old_index).get(
old_index, {}).get('settings', {}))
except elasticsearch.NotFoundError:
s = {}
else:
s = {}
num_replicas = s.get('number_of_replicas',
settings.ES_DEFAULT_NUM_REPLICAS)
num_shards = s.get('number_of_shards',
settings.ES_DEFAULT_NUM_SHARDS)
# Flag the database to mark as currently indexing.
if not chain:
chain = flag_database.si(new_index, old_index, ALIAS)
else:
chain |= flag_database.si(new_index, old_index, ALIAS)
# Create the indexes and mappings.
# Note: We set num_replicas=0 here to lower load while re-indexing.
# In later step we increase it which results in more efficient bulk
# copy in ES. For ES < 0.90 we manually enable compression.
chain |= create_index.si(new_index, ALIAS, INDEXER, {
'analysis': INDEXER.get_analysis(),
'number_of_replicas': 0, 'number_of_shards': num_shards,
'store.compress.tv': True, 'store.compress.stored': True,
'refresh_interval': '-1'})
# Index all the things!
chain |= run_indexing.si(new_index, INDEXER, CHUNK_SIZE)
# After indexing we optimize the index, adjust settings, and point
# alias to the new index.
chain |= update_alias.si(new_index, old_index, ALIAS, {
'number_of_replicas': num_replicas, 'refresh_interval': '5s'})
# Unflag the database to mark as done indexing.
chain |= unflag_database.si()
# Delete the old index, if any.
for old_index in old_indexes:
if old_index:
chain |= delete_index.si(old_index)
# All done!
chain |= output_summary.si()
# Ship it.
self.stdout.write('\nNew index and indexing tasks all queued up.\n')
os.environ['FORCE_INDEXING'] = '1'
try:
chain.apply_async()
finally:
del os.environ['FORCE_INDEXING']
def handle(self, *args, **kwargs):
"""Set up reindexing tasks.
Creates a Tasktree that creates a new indexes and indexes all objects,
then points the alias to this new index when finished.
"""
global INDEXES
index_choice = kwargs.get('index', None)
prefix = kwargs.get('prefix', '')
force = kwargs.get('force', False)
if index_choice:
# If we only want to reindex a subset of indexes.
INDEXES = INDEX_DICT.get(index_choice, INDEXES)
if Reindexing.is_reindexing() and not force:
raise CommandError('Indexation already occuring - use --force to '
'bypass')
elif force:
Reindexing.unflag_reindexing()
for ALIAS, INDEXER, CHUNK_SIZE in INDEXES:
chunks, total = chunk_indexing(INDEXER, CHUNK_SIZE)
if not total:
_print('No items to queue.', ALIAS)
else:
total_chunks = int(ceil(total / float(CHUNK_SIZE)))
_print('Indexing {total} items into {n} chunks of size {size}'
.format(total=total, n=total_chunks, size=CHUNK_SIZE),
ALIAS)
# Get the old index if it exists.
try:
aliases = ES.indices.get_alias(name=ALIAS).keys()
except elasticsearch.NotFoundError:
aliases = []
old_index = aliases[0] if aliases else None
# Create a new index, using the index name with a timestamp.
new_index = timestamp_index(prefix + ALIAS)
# See how the index is currently configured.
if old_index:
try:
s = (ES.indices.get_settings(index=old_index).get(
old_index, {}).get('settings', {}))
except elasticsearch.NotFoundError:
s = {}
else:
s = {}
num_replicas = s.get('number_of_replicas',
settings.ES_DEFAULT_NUM_REPLICAS)
num_shards = s.get('number_of_shards',
settings.ES_DEFAULT_NUM_SHARDS)
pre_task = pre_index.si(new_index, old_index, ALIAS, INDEXER, {
'analysis': INDEXER.get_analysis(),
'number_of_replicas': 0,
'number_of_shards': num_shards,
'store.compress.tv': True,
'store.compress.stored': True,
'refresh_interval': '-1'})
post_task = post_index.si(new_index, old_index, ALIAS, INDEXER, {
'number_of_replicas': num_replicas,
'refresh_interval': '5s'})
# Ship it.
if not total:
# If there's no data we still create the index and alias.
chain(pre_task, post_task).apply_async()
else:
index_tasks = [run_indexing.si(new_index, INDEXER, chunk)
for chunk in chunks]
chain(pre_task,
chord(header=index_tasks, body=post_task)).apply_async()
_print('New index and indexing tasks all queued up.')