feat(uti): Data source

Signed-off-by: Peter Mikus <pmikus@cisco.com>
Change-Id: Idbd1f0f5a4b08909c2c8e783da62024c850ec90a

2 files changed, 289 insertions, 15 deletions

diff --git a/resources/tools/dash/app/pal/report/data.py b/resources/tools/dash/app/pal/report/data.py
index 43e0239228..848259be4a 100644
--- a/resources/tools/dash/app/pal/report/data.py
+++ b/resources/tools/dash/app/pal/report/data.py
@@ -13,14 +13,256 @@
 
 """Prepare data for Plotly Dash."""
 
-import pandas as pd
+from logging import info
+from time import time
 
+import awswrangler as wr
+from awswrangler.exceptions import EmptyDataFrame, NoFilesFound
+from boto3 import session
 
-def create_dataframe():
-    """Create Pandas DataFrame from local CSV.
+
+S3_DOCS_BUCKET="fdio-docs-s3-cloudfront-index"
+
+def create_dataframe_from_parquet(
+        path, partition_filter=None, columns=None,
+        validate_schema=False, last_modified_begin=None,
+        last_modified_end=None):
+    """Read parquet stored in S3 compatible storage and returns Pandas
+    Dataframe.
+
+    :param path: S3 prefix (accepts Unix shell-style wildcards) (e.g.
+        s3://bucket/prefix) or list of S3 objects paths (e.g. [s3://bucket/key0,
+        s3://bucket/key1]).
+    :param partition_filter: Callback Function filters to apply on PARTITION
+        columns (PUSH-DOWN filter). This function MUST receive a single argument
+        (Dict[str, str]) where keys are partitions names and values are
+        partitions values. Partitions values will be always strings extracted
+        from S3. This function MUST return a bool, True to read the partition or
+        False to ignore it. Ignored if dataset=False.
+    :param columns: Names of columns to read from the file(s).
+    :param validate_schema: Check that individual file schemas are all the
+        same / compatible. Schemas within a folder prefix should all be the
+        same. Disable if you have schemas that are different and want to disable
+        this check.
+    :param last_modified_begin: Filter the s3 files by the Last modified date of
+        the object. The filter is applied only after list all s3 files.
+    :param last_modified_end: Filter the s3 files by the Last modified date of
+        the object. The filter is applied only after list all s3 files.
+    :type path: Union[str, List[str]]
+    :type partition_filter: Callable[[Dict[str, str]], bool], optional
+    :type columns: List[str], optional
+    :type validate_schema: bool, optional
+    :type last_modified_begin: datetime, optional
+    :type last_modified_end: datetime, optional
+    :returns: Pandas DataFrame or None if DataFrame cannot be fetched.
+    :rtype: DataFrame
+    """
+    df = None
+    start = time()
+    try:
+        df = wr.s3.read_parquet(
+            path=path,
+            path_suffix="parquet",
+            ignore_empty=True,
+            validate_schema=validate_schema,
+            use_threads=True,
+            dataset=True,
+            columns=columns,
+            partition_filter=partition_filter,
+            last_modified_begin=last_modified_begin,
+            last_modified_end=last_modified_end
+        )
+        info(f"Create dataframe {path} took: {time() - start}")
+        info(df)
+        info(df.info(memory_usage="deep"))
+    except NoFilesFound:
+        return df
+
+    return df
+
+
+def read_stats():
+    """Read Suite Result Analysis data partition from parquet.
+    """
+    lambda_f = lambda part: True if part["stats_type"] == "sra" else False
+
+    return create_dataframe_from_parquet(
+        path=f"s3://{S3_DOCS_BUCKET}/csit/parquet/stats",
+        partition_filter=lambda_f
+    )
+
+def read_trending_mrr():
+    """Read MRR data partition from parquet.
+    """
+    lambda_f = lambda part: True if part["test_type"] == "mrr" else False
+
+    return create_dataframe_from_parquet(
+        path=f"s3://{S3_DOCS_BUCKET}/csit/parquet/trending",
+        partition_filter=lambda_f,
+        columns=["job", "build", "dut_type", "dut_version", "hosts",
+            "start_time", "passed", "test_id", "test_name_long",
+            "test_name_short", "version",
+            "result_receive_rate_rate_avg",
+            "result_receive_rate_rate_stdev",
+            "result_receive_rate_rate_unit",
+            "result_receive_rate_rate_values"
+        ]
+    )
+
+def read_iterative_mrr():
+    """Read MRR data partition from iterative parquet.
+    """
+    lambda_f = lambda part: True if part["test_type"] == "mrr" else False
+
+    return create_dataframe_from_parquet(
+        path=f"s3://{S3_DOCS_BUCKET}/csit/parquet/iterative_rls2202",
+        partition_filter=lambda_f,
+        columns=["job", "build", "dut_type", "dut_version", "hosts",
+            "start_time", "passed", "test_id", "test_name_long",
+            "test_name_short", "version",
+            "result_receive_rate_rate_avg",
+            "result_receive_rate_rate_stdev",
+            "result_receive_rate_rate_unit",
+            "result_receive_rate_rate_values"
+        ]
+    )
+
+def read_trending_ndrpdr():
+    """Read NDRPDR data partition from iterative parquet.
+    """
+    lambda_f = lambda part: True if part["test_type"] == "ndrpdr" else False
+
+    return create_dataframe_from_parquet(
+        path=f"s3://{S3_DOCS_BUCKET}/csit/parquet/trending",
+        partition_filter=lambda_f,
+        columns=["job", "build", "dut_type", "dut_version", "hosts",
+            "start_time", "passed", "test_id", "test_name_long",
+            "test_name_short", "version",
+            "result_pdr_upper_rate_unit",
+            "result_pdr_upper_rate_value",
+            "result_pdr_upper_bandwidth_unit",
+            "result_pdr_upper_bandwidth_value",
+            "result_pdr_lower_rate_unit",
+            "result_pdr_lower_rate_value",
+            "result_pdr_lower_bandwidth_unit",
+            "result_pdr_lower_bandwidth_value",
+            "result_ndr_upper_rate_unit",
+            "result_ndr_upper_rate_value",
+            "result_ndr_upper_bandwidth_unit",
+            "result_ndr_upper_bandwidth_value",
+            "result_ndr_lower_rate_unit",
+            "result_ndr_lower_rate_value",
+            "result_ndr_lower_bandwidth_unit",
+            "result_ndr_lower_bandwidth_value",
+            "result_latency_reverse_pdr_90_avg",
+            "result_latency_reverse_pdr_90_hdrh",
+            "result_latency_reverse_pdr_90_max",
+            "result_latency_reverse_pdr_90_min",
+            "result_latency_reverse_pdr_90_unit",
+            "result_latency_reverse_pdr_50_avg",
+            "result_latency_reverse_pdr_50_hdrh",
+            "result_latency_reverse_pdr_50_max",
+            "result_latency_reverse_pdr_50_min",
+            "result_latency_reverse_pdr_50_unit",
+            "result_latency_reverse_pdr_10_avg",
+            "result_latency_reverse_pdr_10_hdrh",
+            "result_latency_reverse_pdr_10_max",
+            "result_latency_reverse_pdr_10_min",
+            "result_latency_reverse_pdr_10_unit",
+            "result_latency_reverse_pdr_0_avg",
+            "result_latency_reverse_pdr_0_hdrh",
+            "result_latency_reverse_pdr_0_max",
+            "result_latency_reverse_pdr_0_min",
+            "result_latency_reverse_pdr_0_unit",
+            "result_latency_forward_pdr_90_avg",
+            "result_latency_forward_pdr_90_hdrh",
+            "result_latency_forward_pdr_90_max",
+            "result_latency_forward_pdr_90_min",
+            "result_latency_forward_pdr_90_unit",
+            "result_latency_forward_pdr_50_avg",
+            "result_latency_forward_pdr_50_hdrh",
+            "result_latency_forward_pdr_50_max",
+            "result_latency_forward_pdr_50_min",
+            "result_latency_forward_pdr_50_unit",
+            "result_latency_forward_pdr_10_avg",
+            "result_latency_forward_pdr_10_hdrh",
+            "result_latency_forward_pdr_10_max",
+            "result_latency_forward_pdr_10_min",
+            "result_latency_forward_pdr_10_unit",
+            "result_latency_forward_pdr_0_avg",
+            "result_latency_forward_pdr_0_hdrh",
+            "result_latency_forward_pdr_0_max",
+            "result_latency_forward_pdr_0_min",
+            "result_latency_forward_pdr_0_unit"
+        ]
+    )
+
+def read_iterative_ndrpdr():
+    """Read NDRPDR data partition from parquet.
     """
+    lambda_f = lambda part: True if part["test_type"] == "ndrpdr" else False
 
-    return pd.read_csv(
-        u"https://s3-docs.fd.io/csit/master/trending/_static/vpp/"
-        u"csit-vpp-perf-mrr-daily-master-2n-skx-trending.csv"
+    return create_dataframe_from_parquet(
+        path=f"s3://{S3_DOCS_BUCKET}/csit/parquet/iterative_rls2202",
+        partition_filter=lambda_f,
+        columns=["job", "build", "dut_type", "dut_version", "hosts",
+            "start_time", "passed", "test_id", "test_name_long",
+            "test_name_short", "version",
+            "result_pdr_upper_rate_unit",
+            "result_pdr_upper_rate_value",
+            "result_pdr_upper_bandwidth_unit",
+            "result_pdr_upper_bandwidth_value",
+            "result_pdr_lower_rate_unit",
+            "result_pdr_lower_rate_value",
+            "result_pdr_lower_bandwidth_unit",
+            "result_pdr_lower_bandwidth_value",
+            "result_ndr_upper_rate_unit",
+            "result_ndr_upper_rate_value",
+            "result_ndr_upper_bandwidth_unit",
+            "result_ndr_upper_bandwidth_value",
+            "result_ndr_lower_rate_unit",
+            "result_ndr_lower_rate_value",
+            "result_ndr_lower_bandwidth_unit",
+            "result_ndr_lower_bandwidth_value",
+            "result_latency_reverse_pdr_90_avg",
+            "result_latency_reverse_pdr_90_hdrh",
+            "result_latency_reverse_pdr_90_max",
+            "result_latency_reverse_pdr_90_min",
+            "result_latency_reverse_pdr_90_unit",
+            "result_latency_reverse_pdr_50_avg",
+            "result_latency_reverse_pdr_50_hdrh",
+            "result_latency_reverse_pdr_50_max",
+            "result_latency_reverse_pdr_50_min",
+            "result_latency_reverse_pdr_50_unit",
+            "result_latency_reverse_pdr_10_avg",
+            "result_latency_reverse_pdr_10_hdrh",
+            "result_latency_reverse_pdr_10_max",
+            "result_latency_reverse_pdr_10_min",
+            "result_latency_reverse_pdr_10_unit",
+            "result_latency_reverse_pdr_0_avg",
+            "result_latency_reverse_pdr_0_hdrh",
+            "result_latency_reverse_pdr_0_max",
+            "result_latency_reverse_pdr_0_min",
+            "result_latency_reverse_pdr_0_unit",
+            "result_latency_forward_pdr_90_avg",
+            "result_latency_forward_pdr_90_hdrh",
+            "result_latency_forward_pdr_90_max",
+            "result_latency_forward_pdr_90_min",
+            "result_latency_forward_pdr_90_unit",
+            "result_latency_forward_pdr_50_avg",
+            "result_latency_forward_pdr_50_hdrh",
+            "result_latency_forward_pdr_50_max",
+            "result_latency_forward_pdr_50_min",
+            "result_latency_forward_pdr_50_unit",
+            "result_latency_forward_pdr_10_avg",
+            "result_latency_forward_pdr_10_hdrh",
+            "result_latency_forward_pdr_10_max",
+            "result_latency_forward_pdr_10_min",
+            "result_latency_forward_pdr_10_unit",
+            "result_latency_forward_pdr_0_avg",
+            "result_latency_forward_pdr_0_hdrh",
+            "result_latency_forward_pdr_0_max",
+            "result_latency_forward_pdr_0_min",
+            "result_latency_forward_pdr_0_unit"
+        ]
     )
diff --git a/resources/tools/dash/app/pal/report/report.py b/resources/tools/dash/app/pal/report/report.py
index d22a0b6705..769a6dd63e 100644
--- a/resources/tools/dash/app/pal/report/report.py
+++ b/resources/tools/dash/app/pal/report/report.py
@@ -18,10 +18,10 @@ import dash
 from dash import dcc
 from dash import html
 from dash import dash_table
-import numpy as np
-import pandas as pd
 
-from .data import create_dataframe
+from .data import read_stats
+from .data import read_trending_mrr, read_trending_ndrpdr
+from .data import read_iterative_mrr, read_iterative_ndrpdr
 from .layout import html_layout
 
 
@@ -43,34 +43,66 @@ def init_report(server):
         ],
     )
 
-    # Load DataFrame
-    df = create_dataframe()
-
     # Custom HTML layout
     dash_app.index_string = html_layout
 
     # Create Layout
     dash_app.layout = html.Div(
         children=[
-            create_data_table(df),
+            html.Div(
+                children=create_data_table(
+                    read_stats().dropna(),
+                    u"database-table-stats"
+                )
+            ),
+            html.Div(
+                children=create_data_table(
+                    read_trending_mrr().dropna(),
+                    u"database-table-mrr"
+                )
+            ),
+            html.Div(
+                children=create_data_table(
+                    read_trending_ndrpdr().dropna(),
+                    u"database-table-ndrpdr"
+                )
+            ),
+            html.Div(
+                children=create_data_table(
+                    read_iterative_mrr().dropna(),
+                    u"database-table-iterative-mrr"
+                )
+            ),
+            html.Div(
+                children=create_data_table(
+                    read_iterative_ndrpdr().dropna(),
+                    u"database-table-iterative-ndrpdr"
+                )
+            )
         ],
         id=u"dash-container",
     )
     return dash_app.server
 
 
-def create_data_table(df):
+def create_data_table(df, id):
     """Create Dash datatable from Pandas DataFrame.
 
     DEMO
     """
 
     table = dash_table.DataTable(
-        id=u"database-table",
+        id=id,
         columns=[{u"name": i, u"id": i} for i in df.columns],
         data=df.to_dict(u"records"),
+        fixed_rows={'headers': True},
         sort_action=u"native",
         sort_mode=u"native",
         page_size=5,
+        style_header={
+            'overflow': 'hidden',
+            'textOverflow': 'ellipsis',
+            'minWidth': 95, 'maxWidth': 95, 'width': 95,
+        }
     )
     return table