218 lines
7.7 KiB
Python
218 lines
7.7 KiB
Python
from itertools import islice
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from operator import methodcaller
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try:
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from itertools import imap as map
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except ImportError:
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pass # python 3, use builtin map
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from elasticsearch.exceptions import ElasticsearchException
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class BulkIndexError(ElasticsearchException):
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@property
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def errors(self):
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""" List of errors from execution of the last chunk. """
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return self.args[1]
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def expand_action(data):
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"""
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From one document or action definition passed in by the user extract the
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action/data lines needed for elasticsearch's
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:meth:`~elasticsearch.Elasticsearch.bulk` api.
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"""
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# make sure we don't alter the action
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data = data.copy()
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op_type = data.pop('_op_type', 'index')
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action = {op_type: {}}
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for key in ('_index', '_parent', '_percolate', '_routing', '_timestamp',
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'_ttl', '_type', '_version', '_id', '_retry_on_conflict'):
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if key in data:
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action[op_type][key] = data.pop(key)
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# no data payload for delete
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if op_type == 'delete':
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return action, None
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return action, data.get('_source', data)
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def streaming_bulk(client, actions, chunk_size=500, raise_on_error=False, expand_action_callback=expand_action, **kwargs):
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"""
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Streaming bulk consumes actions from the iterable passed in and yields
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results per action. For non-streaming usecases use
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:func:`~elasticsearch.helpers.bulk` which is a wrapper around streaming
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bulk that returns summary information about the bulk operation once the
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entire input is consumed and sent.
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This function expects the action to be in the format as returned by
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:meth:`~elasticsearch.Elasticsearch.search`, for example::
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{
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'_index': 'index-name',
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'_type': 'document',
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'_id': 42,
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'_parent': 5,
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'_ttl': '1d',
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'_source': {
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...
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}
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}
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Alternatively, if `_source` is not present, it will pop all metadata fields
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from the doc and use the rest as the document data.
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Alternative actions (`_op_type` field defaults to `index`) can be sent as
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well::
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{
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'_op_type': 'delete',
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'_index': 'index-name',
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'_type': 'document',
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'_id': 42,
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}
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{
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'_op_type': 'update',
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'_index': 'index-name',
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'_type': 'document',
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'_id': 42,
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'doc': {'question': 'The life, universe and everything.'}
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}
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:arg client: instance of :class:`~elasticsearch.Elasticsearch` to use
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:arg actions: iterable containing the actions to be executed
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:arg chunk_size: number of docs in one chunk sent to es (default: 500)
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:arg raise_on_error: raise `BulkIndexError` containing errors (as `.errors`
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from the execution of the last chunk)
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:arg expand_action_callback: callback executed on each action passed in,
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should return a tuple containing the action line and the data line
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(`None` if data line should be omitted).
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"""
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actions = map(expand_action_callback, actions)
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# if raise on error is set, we need to collect errors per chunk before raising them
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errors = []
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while True:
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chunk = islice(actions, chunk_size)
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bulk_actions = []
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for action, data in chunk:
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bulk_actions.append(action)
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if data is not None:
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bulk_actions.append(data)
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if not bulk_actions:
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return
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# send the actual request
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resp = client.bulk(bulk_actions, **kwargs)
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# go through request-reponse pairs and detect failures
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for op_type, item in map(methodcaller('popitem'), resp['items']):
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ok = item.get('ok')
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if not ok and raise_on_error:
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errors.append({op_type: item})
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if not errors:
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# if we are not just recording all errors to be able to raise
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# them all at once, yield items individually
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yield ok, {op_type: item}
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if errors:
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raise BulkIndexError('%i document(s) failed to index.' % len(errors), errors)
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def bulk(client, actions, stats_only=False, **kwargs):
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"""
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Helper for the :meth:`~elasticsearch.Elasticsearch.bulk` api that provides
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a more human friendly interface - it consumes an iterator of actions and
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sends them to elasticsearch in chunks. It returns a tuple with summary
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information - number of successfully executed actions and either list of
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errors or number of errors if `stats_only` is set to `True`.
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See :func:`~elasticsearch.helpers.streaming_bulk` for more information
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and accepted formats.
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:arg client: instance of :class:`~elasticsearch.Elasticsearch` to use
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:arg actions: iterator containing the actions
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:arg stats_only: if `True` only report number of successful/failed
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operations instead of just number of successful and a list of error responses
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Any additional keyword arguments will be passed to
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:func:`~elasticsearch.helpers.streaming_bulk` which is used to execute
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the operation.
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"""
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success, failed = 0, 0
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# list of errors to be collected is not stats_only
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errors = []
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for ok, item in streaming_bulk(client, actions, **kwargs):
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# go through request-reponse pairs and detect failures
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if not ok:
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if not stats_only:
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errors.append(item)
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failed += 1
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else:
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success += 1
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return success, failed if stats_only else errors
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# preserve the name for backwards compatibility
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bulk_index = bulk
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def scan(client, query=None, scroll='5m', **kwargs):
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"""
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Simple abstraction on top of the
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:meth:`~elasticsearch.Elasticsearch.scroll` api - a simple iterator that
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yields all hits as returned by underlining scroll requests.
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:arg client: instance of :class:`~elasticsearch.Elasticsearch` to use
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:arg query: body for the :meth:`~elasticsearch.Elasticsearch.search` api
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:arg scroll: Specify how long a consistent view of the index should be
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maintained for scrolled search
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Any additional keyword arguments will be passed to the initial
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:meth:`~elasticsearch.Elasticsearch.search` call.
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"""
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# initial search to
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resp = client.search(body=query, search_type='scan', scroll=scroll, **kwargs)
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scroll_id = resp['_scroll_id']
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while True:
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resp = client.scroll(scroll_id, scroll=scroll)
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if not resp['hits']['hits']:
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break
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for hit in resp['hits']['hits']:
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yield hit
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scroll_id = resp['_scroll_id']
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def reindex(client, source_index, target_index, target_client=None, chunk_size=500, scroll='5m'):
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"""
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Reindex all documents from one index to another, potentially (if
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`target_client` is specified) on a different cluster.
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.. note::
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This helper doesn't transfer mappings, just the data.
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:arg client: instance of :class:`~elasticsearch.Elasticsearch` to use (for
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read if `target_client` is specified as well)
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:arg source_index: index (or list of indices) to read documents from
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:arg target_index: name of the index in the target cluster to populate
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:arg target_client: optional, is specified will be used for writing (thus
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enabling reindex between clusters)
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:arg chunk_size: number of docs in one chunk sent to es (default: 500)
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:arg scroll: Specify how long a consistent view of the index should be
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maintained for scrolled search
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"""
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target_client = client if target_client is None else target_client
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docs = scan(client, index=source_index, scroll=scroll)
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def _change_doc_index(hits, index):
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for h in hits:
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h['_index'] = index
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yield h
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return bulk(target_client, _change_doc_index(docs, target_index),
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chunk_size=chunk_size, stats_only=True)
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