Python elasticsearch_dsl.DocType方法代碼示例

# 需要導入模塊: import elasticsearch_dsl [as 別名]
# 或者: from elasticsearch_dsl import DocType [as 別名]
def restore_tokens():
    connections.create_connection(hosts=ES_NODES)
    Index(INDEX_NAME).delete()

    class Token(DocType):
        username = String()
        token = String()
        expires = Date()
        read = Boolean()
        write = Boolean()
        revoked = Boolean()
        acl = String()
        groups = String()
        admin = Boolean()
        last_activity_at = Date()

        class Meta:
            index = INDEX_NAME

    Token.init()
    reindex_results = connections.get_connection().reindex(body={"source": {"index": BACKUP_INDEX_NAME}, "dest": {"index": INDEX_NAME}}, request_timeout=3600)
    if reindex_results.get('created') + reindex_results.get('updated') == reindex_results.get('total'):
        return ('Tokens restored to previous schema successfully!')
    else:
        return ('Tokens did not restore from backup properly') 

# 需要導入模塊: import elasticsearch_dsl [as 別名]
# 或者: from elasticsearch_dsl import DocType [as 別名]
def _find_field_template(self, field_name):
        """
        finds and sets the default template instance for the given field name with the given template.
        """
        search_templates = []
        if field_name in self.field_templates:
            search_templates.append(self.field_templates[field_name])
        for _cls in inspect.getmro(self.document):
            if issubclass(_cls, dsl.DocType):
                search_templates.append('seeker/%s/%s.html' % (_cls._doc_type.name, field_name))
        search_templates.append('seeker/column.html')
        template = loader.select_template(search_templates)
        existing_templates = list(set(self._field_templates.values()))
        for existing_template in existing_templates:
            #If the template object already exists just re-use the existing one.
            if template.template.name == existing_template.template.name:
                template = existing_template
                break
        self._field_templates.update({field_name: template})
        return template 

# 需要導入模塊: import elasticsearch_dsl [as 別名]
# 或者: from elasticsearch_dsl import DocType [as 別名]
def setup_collection(self):
        class WebLink(DocType):
            url = Text()
            html = Text()
            headers = Text()
            status = Integer()
            created = Date()

            class Meta:
                index = self.database_name
                doc_type = self.collection_name

        return WebLink 

# 需要導入模塊: import elasticsearch_dsl [as 別名]
# 或者: from elasticsearch_dsl import DocType [as 別名]
def setup_collection(self):
        class WebLinkExtracted(DocType):
            url = Text()
            body = Text()
            headers = Text()
            status = Integer()
            created = Date()

            class Meta:
                index = self.database_name
                doc_type = self.collection_name

        return WebLinkExtracted 

# 需要導入模塊: import elasticsearch_dsl [as 別名]
# 或者: from elasticsearch_dsl import DocType [as 別名]
def test_elasticsearch_origin(sdc_builder, sdc_executor, elasticsearch):
    """Test for Elasticsearch origin stage. We do so by putting data via Elastisearch client and reading via
    Elastisearch origin pipeline. To assert, we will snapshot the pipeline.
    The pipeline looks like:

    Elasticsearch origin pipeline:
        es_origin >> trash
    """
    es_index = get_random_string(string.ascii_letters, 10).lower()  # Elasticsearch indexes must be lower case
    es_doc_id = get_random_string(string.ascii_letters, 10)
    raw_str = 'Hello World!'

    builder = sdc_builder.get_pipeline_builder()
    es_origin = builder.add_stage('Elasticsearch', type='origin')
    es_origin.set_attributes(index=es_index, query="{'query': {'match_all': {}}}")
    trash = builder.add_stage('Trash')

    es_origin >> trash
    es_origin_pipeline = builder.build(title='ES origin pipeline').configure_for_environment(elasticsearch)
    sdc_executor.add_pipeline(es_origin_pipeline)

    try:
        # Put data to Elasticsearch
        elasticsearch.connect()
        doc_type = DocType(meta={'id': es_doc_id, 'index': es_index})
        doc_type.body = raw_str
        doc_type.save()  # save document to Elasticsearch
        index = Index(es_index)
        assert index.refresh()  # assert to refresh index, making all operations available for search

        # Run pipeline and assert
        snapshot = sdc_executor.capture_snapshot(es_origin_pipeline, start_pipeline=True).snapshot
        # no need to stop pipeline - as ES origin shuts off once data is read from Elasticsearch
        snapshot_data = snapshot[es_origin.instance_name].output[0].field
        # assert ES meta
        assert snapshot_data['_index'].value == es_index and snapshot_data['_id'].value == es_doc_id
        # assert ES data
        assert snapshot_data['_source']['body'].value == raw_str
    finally:
        # Clean up test data in ES
        idx = Index(es_index)
        idx.delete() 

# 需要導入模塊: import elasticsearch_dsl [as 別名]
# 或者: from elasticsearch_dsl import DocType [as 別名]
def test_offset_upgrade(sdc_builder, sdc_executor, elasticsearch):
    """Ensure that when upgrading from older offset format (that can be generated by either SCH or by upgrading
       pre-multithreaded pipeline) we properly upgrade the offset and the pipeline will not re-read everything
       from the source.
    """
    es_index = get_random_string(string.ascii_letters, 10).lower()
    es_doc_id = get_random_string(string.ascii_letters, 10)
    raw_str = 'Hello World!'

    builder = sdc_builder.get_pipeline_builder()
    es_origin = builder.add_stage('Elasticsearch', type='origin')
    es_origin.set_attributes(index=es_index, query="{'query': {'match_all': {}}}")
    trash = builder.add_stage('Trash')

    es_origin >> trash
    pipeline = builder.build().configure_for_environment(elasticsearch)
    sdc_executor.add_pipeline(pipeline)

    # We hard code offset to be pre-migration to multi-threaded origin and thus forcing the origin to upgrade it
    offset = {
        'offsets': {
            '$com.streamsets.datacollector.pollsource.offset$': None,
        },
        'version': 2
    }
    sdc_executor.api_client.update_pipeline_committed_offsets(pipeline.id, body=offset)

    try:
        # Put data to Elasticsearch
        elasticsearch.connect()
        doc_type = DocType(meta={'id': es_doc_id, 'index': es_index})
        doc_type.body = raw_str
        doc_type.save()  # save document to Elasticsearch
        index = Index(es_index)
        assert index.refresh()  # assert to refresh index, making all operations available for search

        # Run pipeline and assert
        snapshot = sdc_executor.capture_snapshot(pipeline, start_pipeline=True).snapshot
        # no need to stop pipeline - as ES origin shuts off once data is read from Elasticsearch
        snapshot_data = snapshot[es_origin.instance_name].output[0].field
        # assert ES meta
        assert snapshot_data['_index'] == es_index and snapshot_data['_id'] == es_doc_id
        # assert ES data
        assert snapshot_data['_source']['body'] == raw_str

        # Now let's validate that the offset doesn't have the poll key any more
        offset = sdc_executor.api_client.get_pipeline_committed_offsets(pipeline.id).response.json()
        assert offset is not None
        assert '$com.streamsets.datacollector.pollsource.offset$' not in offset['offsets']
    finally:
        # Clean up test data in ES
        idx = Index(es_index)
        idx.delete()