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#
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from airflow import DAG
from airflow.providers.yandex.operators.yandexcloud_dataproc import (
    DataprocCreateClusterOperator,
    DataprocCreateHiveJobOperator,
    DataprocCreateMapReduceJobOperator,
    DataprocCreatePysparkJobOperator,
    DataprocCreateSparkJobOperator,
    DataprocDeleteClusterOperator,
)
from airflow.utils.dates import days_ago

# should be filled with appropriate ids

# Airflow connection with type "yandexcloud" must be created.
# By default connection with id "yandexcloud_default" will be used
CONNECTION_ID = "yandexcloud_default"

# Name of the datacenter where Dataproc cluster will be created
AVAILABILITY_ZONE_ID = "ru-central1-c"

# Dataproc cluster jobs will produce logs in specified s3 bucket
S3_BUCKET_NAME_FOR_JOB_LOGS = ""


default_args = {
    "owner": "airflow",
}

with DAG(
    "example_yandexcloud_dataproc_operator",
    default_args=default_args,
    schedule_interval=None,
    start_date=days_ago(1),
    tags=["example"],
) as dag:
    create_cluster = DataprocCreateClusterOperator(
        task_id="create_cluster",
        zone=AVAILABILITY_ZONE_ID,
        connection_id=CONNECTION_ID,
        s3_bucket=S3_BUCKET_NAME_FOR_JOB_LOGS,
    )

    create_hive_query = DataprocCreateHiveJobOperator(
        task_id="create_hive_query",
        query="SELECT 1;",
    )

    create_hive_query_from_file = DataprocCreateHiveJobOperator(
        task_id="create_hive_query_from_file",
        query_file_uri="s3a://data-proc-public/jobs/sources/hive-001/main.sql",
        script_variables={
            "CITIES_URI": "s3a://data-proc-public/jobs/sources/hive-001/cities/",
            "COUNTRY_CODE": "RU",
        },
    )

    create_mapreduce_job = DataprocCreateMapReduceJobOperator(
        task_id="create_mapreduce_job",
        main_class="org.apache.hadoop.streaming.HadoopStreaming",
        file_uris=[
            "s3a://data-proc-public/jobs/sources/mapreduce-001/mapper.py",
            "s3a://data-proc-public/jobs/sources/mapreduce-001/reducer.py",
        ],
        args=[
            "-mapper",
            "mapper.py",
            "-reducer",
            "reducer.py",
            "-numReduceTasks",
            "1",
            "-input",
            "s3a://data-proc-public/jobs/sources/data/cities500.txt.bz2",
            "-output",
            f"s3a://{S3_BUCKET_NAME_FOR_JOB_LOGS}/dataproc/job/results",
        ],
        properties={
            "yarn.app.mapreduce.am.resource.mb": "2048",
            "yarn.app.mapreduce.am.command-opts": "-Xmx2048m",
            "mapreduce.job.maps": "6",
        },
    )

    create_spark_job = DataprocCreateSparkJobOperator(
        task_id="create_spark_job",
        main_jar_file_uri="s3a://data-proc-public/jobs/sources/java/dataproc-examples-1.0.jar",
        main_class="ru.yandex.cloud.dataproc.examples.PopulationSparkJob",
        file_uris=[
            "s3a://data-proc-public/jobs/sources/data/config.json",
        ],
        archive_uris=[
            "s3a://data-proc-public/jobs/sources/data/country-codes.csv.zip",
        ],
        jar_file_uris=[
            "s3a://data-proc-public/jobs/sources/java/icu4j-61.1.jar",
            "s3a://data-proc-public/jobs/sources/java/commons-lang-2.6.jar",
            "s3a://data-proc-public/jobs/sources/java/opencsv-4.1.jar",
            "s3a://data-proc-public/jobs/sources/java/json-20190722.jar",
        ],
        args=[
            "s3a://data-proc-public/jobs/sources/data/cities500.txt.bz2",
            f"s3a://{S3_BUCKET_NAME_FOR_JOB_LOGS}/dataproc/job/results/${{JOB_ID}}",
        ],
        properties={
            "spark.submit.deployMode": "cluster",
        },
    )

    create_pyspark_job = DataprocCreatePysparkJobOperator(
        task_id="create_pyspark_job",
        main_python_file_uri="s3a://data-proc-public/jobs/sources/pyspark-001/main.py",
        python_file_uris=[
            "s3a://data-proc-public/jobs/sources/pyspark-001/geonames.py",
        ],
        file_uris=[
            "s3a://data-proc-public/jobs/sources/data/config.json",
        ],
        archive_uris=[
            "s3a://data-proc-public/jobs/sources/data/country-codes.csv.zip",
        ],
        args=[
            "s3a://data-proc-public/jobs/sources/data/cities500.txt.bz2",
            f"s3a://{S3_BUCKET_NAME_FOR_JOB_LOGS}/jobs/results/${{JOB_ID}}",
        ],
        jar_file_uris=[
            "s3a://data-proc-public/jobs/sources/java/dataproc-examples-1.0.jar",
            "s3a://data-proc-public/jobs/sources/java/icu4j-61.1.jar",
            "s3a://data-proc-public/jobs/sources/java/commons-lang-2.6.jar",
        ],
        properties={
            "spark.submit.deployMode": "cluster",
        },
    )

    delete_cluster = DataprocDeleteClusterOperator(
        task_id="delete_cluster",
    )

    create_cluster >> create_mapreduce_job >> create_hive_query >> create_hive_query_from_file
    create_hive_query_from_file >> create_spark_job >> create_pyspark_job >> delete_cluster