lot1-kickoff/airflow/dags/import_EOSC_graph.py

from __future__ import annotations

import gzip
import io
import json
import logging
import os
from datetime import timedelta

from kubernetes.client import models as k8s
import pendulum
from airflow.decorators import dag
from airflow.decorators import task
from airflow.operators.python import PythonOperator
from airflow.providers.amazon.aws.hooks.s3 import S3Hook
from airflow.utils.helpers import chain
from airflow.hooks.base import BaseHook

from opensearchpy import OpenSearch, helpers
from EOSC_indexes import mappings
from EOSC_entity_trasform import transform_entities

EXECUTION_TIMEOUT = int(os.getenv("EXECUTION_TIMEOUT", 6))

default_args = {
    "execution_timeout": timedelta(days=EXECUTION_TIMEOUT),
    "retries": int(os.getenv("DEFAULT_TASK_RETRIES", 1)),
    "retry_delay": timedelta(seconds=int(os.getenv("DEFAULT_RETRY_DELAY_SECONDS", 60))),
}

configs = {
    "all": {"ENTITIES": ["datasource", "grants", "organizations", "persons", "products", "topics", "venues", "interoperability", "services", "training"]},
    "skg-if": {"ENTITIES": ["datasource", "grants", "organizations", "persons", "products", "topics", "venues"]},
    "catalogue": {"ENTITIES": ["interoperability", "services", "training"]},
}

for config_name, config in configs.items():
    dag_id = f"import_EOSC_{config_name}"

    @dag(
        dag_id=dag_id,
        schedule=None,
        dagrun_timeout=None,
        start_date=pendulum.datetime(2021, 1, 1, tz="UTC"),
        catchup=False,
        default_args=default_args,
        params={
            "S3_CONN_ID": "s3_conn",
            "OPENSEARCH_CONN_ID": "opensearch_default",
            "EOSC_CATALOG_BUCKET": "eosc-portal-import",
            "BATCH_LOADERS_NUM": 10,
            "ENTITIES": config["ENTITIES"],
            "SUFFIX": pendulum.now().format('YYYYMMDDHHmmss')
        },
        tags=["lot1"]
    )
    def import_EOSC_entities():
        @task
        def create_indexes(**kwargs):
            conn = BaseHook.get_connection(kwargs["params"]["OPENSEARCH_CONN_ID"])
            client = OpenSearch(
                hosts=[{'host': conn.host, 'port': conn.port}],
                http_auth=(conn.login, conn.password),
                use_ssl=True,
                verify_certs=False,
                ssl_show_warn=False,
                pool_maxsize=20
            )

            client.cluster.put_settings(body={
                "persistent": {
                    "cluster.routing.allocation.balance.prefer_primary": True,
                    "segrep.pressure.enabled": True
                }
            })

            for entity in kwargs["params"]["ENTITIES"]:
                if client.indices.exists(entity):
                    client.indices.delete(entity)

                client.indices.create(entity, {
                    "settings": {
                        "index": {
                            "number_of_shards": 40,
                            "number_of_replicas": 0,
                            "refresh_interval": -1,

                            "translog.flush_threshold_size": "2048MB",

                            "codec": "zstd_no_dict",
                            "replication.type": "SEGMENT"
                        }

                    },
                    "mappings": mappings[entity]
                })

        def compute_batches(ds=None, **kwargs):
            hook = S3Hook(kwargs["params"]["S3_CONN_ID"], transfer_config_args={'use_threads': False})
            pieces = []
            for entity in kwargs["params"]["ENTITIES"]:
                keys = hook.list_keys(bucket_name=kwargs["params"]["EOSC_CATALOG_BUCKET"], prefix=f'{entity}/')
                to_delete = list(filter(lambda key: key.endswith('.PROCESSED'), keys))
                for obj in to_delete:
                    hook.get_conn().delete_object(Bucket=kwargs["params"]["EOSC_CATALOG_BUCKET"], Key=obj)
                for key in keys:
                    if key.endswith('.gz'):
                        pieces.append((entity, key))

            def split_list(list_a, chunk_size):
                for i in range(0, len(list_a), chunk_size):
                    yield {"files": list_a[i:i + chunk_size]}

            num_batches = len(pieces)//kwargs["params"]["BATCH_LOADERS_NUM"]
            if num_batches > 0:
                return list(split_list(pieces, num_batches))
            return pieces

        @task(executor_config={
            "pod_override": k8s.V1Pod(
                spec=k8s.V1PodSpec(
                    containers=[
                        k8s.V1Container(
                            name="base",
                            resources=k8s.V1ResourceRequirements(
                                requests={
                                    "cpu": "550m",
                                    "memory": "256Mi"
                                }
                            )
                        )
                    ]
                )
            )
        })
        def bulk_load(files: list[(str, str)], **kwargs):
            conn = BaseHook.get_connection(kwargs["params"]["OPENSEARCH_CONN_ID"])
            client = OpenSearch(
                hosts=[{'host': conn.host, 'port': conn.port}],
                http_auth=(conn.login, conn.password),
                use_ssl=True,
                verify_certs=False,
                ssl_show_warn=False,
                pool_maxsize=20
            )
            hook = S3Hook(kwargs["params"]["S3_CONN_ID"], transfer_config_args={'use_threads': False})

            for (entity, key) in files:
                if hook.check_for_key(key=f"{key}.PROCESSED", bucket_name=kwargs["params"]["EOSC_CATALOG_BUCKET"]):
                    print(f'Skipping {entity}: {key}')
                    continue
                print(f'Processing {entity}: {key}')
                s3_obj = hook.get_key(key, bucket_name=kwargs["params"]["EOSC_CATALOG_BUCKET"])
                with s3_obj.get()["Body"] as body:
                    with gzip.GzipFile(fileobj=body) as gzipfile:
                        def _generate_data():
                            buff = io.BufferedReader(gzipfile)
                            for line in buff:
                                data = json.loads(line)
                                data['_index'] = entity
                                if entity in transform_entities:
                                    data = transform_entities[entity](data)
                                yield data

                        # disable success post logging
                        logging.getLogger("opensearch").setLevel(logging.WARN)
                        succeeded = 0
                        failed = 0
                        for success, item in helpers.parallel_bulk(client, actions=_generate_data(),
                                                                   raise_on_exception=False,
                                                                   raise_on_error=False,
                                                                   chunk_size=5000,
                                                                   max_chunk_bytes=50 * 1024 * 1024,
                                                                   timeout=180):
                            if success:
                                succeeded = succeeded + 1
                            else:
                                print(item["index"]["error"])
                                failed = failed + 1

                        if failed > 0:
                            print(f"There were {failed} errors:")
                        else:
                            hook.load_string(
                                "",
                                f"{key}.PROCESSED",
                                bucket_name=kwargs["params"]["EOSC_CATALOG_BUCKET"],
                                replace=False
                            )

                        if succeeded > 0:
                            print(f"Bulk-inserted {succeeded} items (streaming_bulk).")

        @task
        def close_indexes(**kwargs):
            conn = BaseHook.get_connection(kwargs["params"]["OPENSEARCH_CONN_ID"])
            client = OpenSearch(
                hosts=[{'host': conn.host, 'port': conn.port}],
                http_auth=(conn.login, conn.password),
                use_ssl=True,
                verify_certs=False,
                ssl_show_warn=False,
                pool_maxsize=20,
                timeout=180
            )
            for entity in kwargs["params"]["ENTITIES"]:
                client.indices.refresh(entity)

        parallel_batches = PythonOperator(task_id="compute_parallel_batches", python_callable=compute_batches)

        chain(
            create_indexes.override(task_id="create_indexes")(),
            parallel_batches,
            bulk_load.expand_kwargs(parallel_batches.output),
            close_indexes.override(task_id="close_indexes")()
        )

    import_EOSC_entities()