1 files changed, 133 insertions, 0 deletions
diff --git a/csit.infra.etl/stats.py b/csit.infra.etl/stats.py
new file mode 100644
index 0000000000..ab8bcafdeb
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+++ b/csit.infra.etl/stats.py
@@ -0,0 +1,133 @@
+#!/usr/bin/env python3
+
+# Copyright (c) 2022 Cisco and/or its affiliates.
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at:
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+"""ETL script running on top of the s3://"""
+
+from datetime import datetime, timedelta
+from json import load
+from os import environ
+from pytz import utc
+
+import awswrangler as wr
+from awswrangler.exceptions import EmptyDataFrame
+from awsglue.context import GlueContext
+from boto3 import session
+from pyspark.context import SparkContext
+from pyspark.sql.functions import lit
+from pyspark.sql.types import StructType
+
+S3_LOGS_BUCKET="fdio-logs-s3-cloudfront-index"
+S3_DOCS_BUCKET="fdio-docs-s3-cloudfront-index"
+PATH=f"s3://{S3_LOGS_BUCKET}/vex-yul-rot-jenkins-1/csit-*-perf-*"
+SUFFIX="suite.info.json.gz"
+IGNORE_SUFFIX=[]
+LAST_MODIFIED_END=utc.localize(
+    datetime.strptime(
+        f"{datetime.now().year}-{datetime.now().month}-{datetime.now().day}",
+        "%Y-%m-%d"
+    )
+)
+LAST_MODIFIED_BEGIN=LAST_MODIFIED_END - timedelta(1)
+
+
+def process_json_to_dataframe(schema_name, paths):
+    """Processes JSON to Spark DataFrame.
+
+    :param schema_name: Schema name.
+    :type schema_name: string
+    :param paths: S3 paths to process.
+    :type paths: list
+    :returns: Spark DataFrame.
+    :rtype: DataFrame
+    """
+    drop_subset = [
+        "duration",
+        "version"
+    ]
+
+    # load schemas
+    with open(f"stats_{schema_name}.json", "r", encoding="UTF-8") as f_schema:
+        schema = StructType.fromJson(load(f_schema))
+
+    # create empty DF out of schemas
+    sdf = spark.createDataFrame([], schema)
+
+    # filter list
+    filtered = [path for path in paths if "tests/suite.info.json.gz" in path]
+
+    # select
+    for path in filtered:
+        print(path)
+
+        sdf_loaded = spark \
+            .read \
+            .option("multiline", "true") \
+            .schema(schema) \
+            .json(path) \
+            .withColumn("job", lit(path.split("/")[4])) \
+            .withColumn("build", lit(path.split("/")[5])) \
+            .withColumn("stats_type", lit(schema_name))
+        sdf = sdf.unionByName(sdf_loaded, allowMissingColumns=True)
+
+    # drop rows with all nulls and drop rows with null in critical frames
+    sdf = sdf.na.drop(how="all")
+    sdf = sdf.na.drop(how="any", thresh=None, subset=drop_subset)
+
+    return sdf
+
+
+# create SparkContext and GlueContext
+spark_context = SparkContext.getOrCreate()
+spark_context.setLogLevel("WARN")
+glue_context = GlueContext(spark_context)
+spark = glue_context.spark_session
+
+# files of interest
+paths = wr.s3.list_objects(
+    path=PATH,
+    suffix=SUFFIX,
+    last_modified_begin=LAST_MODIFIED_BEGIN,
+    last_modified_end=LAST_MODIFIED_END,
+    ignore_suffix=IGNORE_SUFFIX,
+    ignore_empty=True
+)
+
+for schema_name in ["sra"]:
+    out_sdf = process_json_to_dataframe(schema_name, paths)
+    out_sdf.show(truncate=False)
+    out_sdf.printSchema()
+    out_sdf = out_sdf \
+        .withColumn("year", lit(datetime.now().year)) \
+        .withColumn("month", lit(datetime.now().month)) \
+        .withColumn("day", lit(datetime.now().day)) \
+        .repartition(1)
+
+    try:
+        wr.s3.to_parquet(
+            df=out_sdf.toPandas(),
+            path=f"s3://{S3_DOCS_BUCKET}/csit/parquet/stats",
+            dataset=True,
+            partition_cols=["stats_type", "year", "month", "day"],
+            compression="snappy",
+            use_threads=True,
+            mode="overwrite_partitions",
+            boto3_session=session.Session(
+                aws_access_key_id=environ["OUT_AWS_ACCESS_KEY_ID"],
+                aws_secret_access_key=environ["OUT_AWS_SECRET_ACCESS_KEY"],
+                region_name=environ["OUT_AWS_DEFAULT_REGION"]
+            )
+        )
+    except EmptyDataFrame:
+        pass