Recreate the Search Index.

def reindex(self, request):
    """
    Recreate the Search Index.
    """
    r = redis.StrictRedis.from_url(request.registry.settings["celery.scheduler_url"])
    try:
        with SearchLock(r, timeout=30 * 60, blocking_timeout=30):
            p = urllib.parse.urlparse(request.registry.settings["elasticsearch.url"])
            client = elasticsearch.Elasticsearch(
                [urllib.parse.urlunparse(p[:2] + ("",) * 4)],
                verify_certs=True,
                ca_certs=certifi.where(),
                timeout=30,
                retry_on_timeout=True,
                serializer=serializer.serializer,
            )
            number_of_replicas = request.registry.get("elasticsearch.replicas", 0)
            refresh_interval = request.registry.get("elasticsearch.interval", "1s")

            # We use a randomly named index so that we can do a zero downtime reindex.
            # Essentially we'll use a randomly named index which we will use until all
            # of the data has been reindexed, at which point we'll point an alias at
            # our randomly named index, and then delete the old randomly named index.

            # Create the new index and associate all of our doc types with it.
            index_base = request.registry["elasticsearch.index"]
            random_token = binascii.hexlify(os.urandom(5)).decode("ascii")
            new_index_name = "{}-{}".format(index_base, random_token)
            doc_types = request.registry.get("search.doc_types", set())
            shards = request.registry.get("elasticsearch.shards", 1)

            # Create the new index with zero replicas and index refreshes disabled
            # while we are bulk indexing.
            new_index = get_index(
                new_index_name,
                doc_types,
                using=client,
                shards=shards,
                replicas=0,
                interval="-1",
            )
            new_index.create(wait_for_active_shards=shards)

            # From this point on, if any error occurs, we want to be able to delete our
            # in progress index.
            try:
                request.db.execute("SET statement_timeout = '600s'")

                for _ in parallel_bulk(
                    client, _project_docs(request.db), index=new_index_name
                ):
                    pass
            except:  # noqa
                new_index.delete()
                raise
            finally:
                request.db.rollback()
                request.db.close()

            # Now that we've finished indexing all of our data we can update the
            # replicas and refresh intervals.
            client.indices.put_settings(
                index=new_index_name,
                body={
                    "index": {
                        "number_of_replicas": number_of_replicas,
                        "refresh_interval": refresh_interval,
                    }
                },
            )

            # Point the alias at our new randomly named index and delete the old index.
            if client.indices.exists_alias(name=index_base):
                to_delete = set()
                actions = []
                for name in client.indices.get_alias(name=index_base):
                    to_delete.add(name)
                    actions.append({"remove": {"index": name, "alias": index_base}})
                actions.append({"add": {"index": new_index_name, "alias": index_base}})
                client.indices.update_aliases({"actions": actions})
                client.indices.delete(",".join(to_delete))
            else:
                client.indices.put_alias(name=index_base, index=new_index_name)
    except redis.exceptions.LockError as exc:
        raise self.retry(countdown=60, exc=exc)