{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import sqlalchemy\n",
"import pandas as pd\n",
"import numpy as np\n",
"from pathlib import Path\n",
"import cudf\n",
"import colormaps as cm"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [],
"source": [
"hive_dir = '/data/rc/gpfs-policy/data/gpfs-hive/data-project/'\n",
"db = Path('/data/rc/gpfs-policy/data/gpfs-hive/db/data-project.db')\n",
"engine = sqlalchemy.create_engine(f\"sqlite:///{db}\")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"df = pd.read_sql(\"SELECT * FROM churn WHERE prior_log_dt >= '2024-11-14'\",engine)"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [],
"source": [
"df['total_churn'] = df['created'] + df['deleted'] + df['modified']\n",
"df['total_churn_bytes'] = df['created_bytes'] + df['deleted_bytes'] + df['modified_bytes_net']\n",
"df[['log_dt','prior_log_dt']] = df[['log_dt','prior_log_dt']].apply(lambda x: pd.to_datetime(x))\n",
"df['tld'] = df['tld'].astype('category')"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {},
"outputs": [],
"source": [
"tld_agg = df.groupby('tld',observed=True)[['total_churn','total_churn_bytes','accessed','accessed_bytes']].sum().sort_values('total_churn',ascending=False)"
]
},
{
"cell_type": "code",
"execution_count": 91,
"metadata": {},
"outputs": [],
"source": [
"no_churn = tld_agg.loc[tld_agg['total_churn'].eq(0)].index"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"cdf = cudf.read_parquet(hive_dir,filters = [('tld','in',no_churn.to_list()),('acq','==','2025-01-15')],columns=['tld','size','kballoc'],categorical_partitions=True)"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {},
"outputs": [],
"source": [
"cdf['tld'] = cdf['tld'].astype('category')"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"inactive_storage = cdf.groupby('tld',observed=True)[['size','kballoc']].sum()"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"np.float64(447.3787513971329)"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"inactive_storage['kballoc'].divide(1024**3).sum()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Plotting"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [],
"source": [
"import plotly.graph_objects as go\n",
"\n",
"def convert_colormap(rgb):\n",
" r, g, b = (rgb*255).astype(int)\n",
" return f\"rgb({r},{g},{b})\"\n",
"\n",
"colormap = cm.oslo_r.colors\n",
"colorscale = [[i / 255, convert_colormap(colormap[i])] for i in range(256)]"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Churn\n",
"These plots only include the directories where at least one file was churned during the time period. This ignores directories where files were accessed but never changed"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {},
"outputs": [],
"source": [
"active = df.loc[~df['tld'].isin(no_churn.to_list())].copy()\n",
"active['tld'] = active['tld'].cat.remove_unused_categories()"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {},
"outputs": [],
"source": [
"# order by daily activity, percentage of days in the time period where at least one change was made\n",
"order = active.groupby('tld',observed=True)['total_churn'].apply(lambda x: x.ne(0).sum()).sort_values(ascending=False).index.as_ordered()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Total Churn (File Count) Timeseries"
]
},
{
"cell_type": "code",
"execution_count": 197,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mdefende/.conda/envs/gpfs/lib/python3.11/site-packages/pandas/core/arraylike.py:399: RuntimeWarning:\n",
"\n",
"divide by zero encountered in log10\n",
"\n"
]
}
],
"source": [
"fig = go.Figure(\n",
" data = go.Heatmap(\n",
" z = np.log10(active['total_churn']),\n",
" y = active['log_dt'],\n",
" x = active['tld'],\n",
" xgap=2,\n",
" colorscale=colorscale,\n",
" colorbar=dict(\n",
" tickvals=np.arange(0,9),\n",
" ticktext=[str(10**d) for d in np.arange(0,9)],\n",
" tickfont=dict(\n",
" size = 14\n",
" ),\n",
" title=dict(\n",
" text='Churn (files altered)',\n",
" font=dict(\n",
" size = 16\n",
" )\n",
" )\n",
" ),\n",
" hovertemplate='Dir: %{x}<br>Date: %{y}<br>Churn: %{customdata}<extra></extra>',\n",
" customdata=active['total_churn']\n",
" )\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 198,
"metadata": {},
"outputs": [],
"source": [
"fig = fig.update_layout(\n",
" template = 'plotly_white',\n",
" height = 1000,\n",
" width = 2000,\n",
" title_text = 'Time Course of Total Churn For Project Directories Over 2 Months',\n",
" title_x = 0.5,\n",
" title_xanchor = 'center',\n",
" title_font_size = 30,\n",
"\n",
" xaxis = dict(\n",
" title = dict(\n",
" text = 'Directory Name',\n",
" font_size = 20\n",
" ),\n",
" gridwidth = 2,\n",
" showgrid = True,\n",
" gridcolor='black'\n",
" ),\n",
" \n",
" yaxis = dict(\n",
" showgrid = False,\n",
" title = dict(\n",
" text = 'Policy Run Date',\n",
" font_size = 20\n",
" ),\n",
" gridcolor = 'black',\n",
" ),\n",
" \n",
" coloraxis_colorbar=dict(\n",
" title=\"Raw Values\", # Change the title of the z-axis\n",
" titlefont=dict(size=20) # Increase the font size\n",
" ),\n",
"\n",
" margin=dict(t=100, b=20, l=40, r=40)\n",
")\n",
"\n",
"fig = fig.update_xaxes(\n",
" categoryorder='array',\n",
" categoryarray=order,\n",
" tickfont={'size':14},\n",
" ticklabelshift = 3,\n",
" tickson = 'boundaries',\n",
" gridwidth=2\n",
")\n",
"\n",
"fig = fig.update_yaxes(\n",
" tickfont={'size':16},\n",
" tickformat = \"%Y-%m-%d\",\n",
" tick0 = '2024-11-15',\n",
" ticklabelstep=2,\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 199,
"metadata": {},
"outputs": [
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"metadata": {},
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}
],
"source": [
"fig.show()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Total Churn (Bytes) Timeseries"
]
},
{
"cell_type": "code",
"execution_count": 66,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mdefende/.conda/envs/gpfs/lib/python3.11/site-packages/pandas/core/arraylike.py:399: RuntimeWarning:\n",
"\n",
"divide by zero encountered in log2\n",
"\n",
"/home/mdefende/.conda/envs/gpfs/lib/python3.11/site-packages/pandas/core/arraylike.py:399: RuntimeWarning:\n",
"\n",
"invalid value encountered in log2\n",
"\n"
]
}
],
"source": [
"f2 = go.Figure(\n",
" data = go.Heatmap(\n",
" z = np.log2(active['total_churn_bytes']),\n",
" y = active['log_dt'],\n",
" x = active['tld'],\n",
" xgap=2,\n",
" colorscale=colorscale,\n",
" colorbar=dict(\n",
" tickvals=np.log2([1, 1024, 1024**2, 1024**3, 1024**4, 100 * 1024**4]),\n",
" ticktext=['1 B', '1 KiB', '1 MiB', '1 GiB', '1 TiB', '100 TiB'],\n",
" tickmode='array',\n",
" tickfont=dict(\n",
" size = 14\n",
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" title=dict(\n",
" text='Churn (bytes altered)',\n",
" font=dict(\n",
" size = 16\n",
" )\n",
" )\n",
" ),\n",
" hovertemplate='Dir: %{x}<br>Date: %{y}<br>Churn: %{customdata}<extra></extra>',\n",
" customdata=active['total_churn_bytes']\n",
" )\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 67,
"metadata": {},
"outputs": [],
"source": [
"f2 = f2.update_layout(\n",
" template = 'plotly_white',\n",
" height = 1000,\n",
" width = 2000,\n",
" title_text = 'Time Course of Total Churn (Bytes) For Project Directories Over 2 Months',\n",
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" title_xanchor = 'center',\n",
" title_font_size = 30,\n",
"\n",
" xaxis = dict(\n",
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" text = 'Directory Name',\n",
" font_size = 20\n",
" ),\n",
" gridwidth = 2,\n",
" showgrid = True,\n",
" gridcolor='black'\n",
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" yaxis = dict(\n",
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" title = dict(\n",
" text = 'Policy Run Date',\n",
" font_size = 20\n",
" ),\n",
" gridcolor = 'black',\n",
" ),\n",
" \n",
" coloraxis_colorbar=dict(\n",
" title=\"Raw Values\", # Change the title of the z-axis\n",
" titlefont=dict(size=20) # Increase the font size\n",
" ),\n",
"\n",
" margin=dict(t=100, b=20, l=40, r=40)\n",
")\n",
"\n",
"f2 = f2.update_xaxes(\n",
" categoryorder='array',\n",
" categoryarray=order,\n",
" tickfont={'size':14},\n",
" ticklabelshift = 3,\n",
" tickson = 'boundaries',\n",
" gridwidth=2\n",
")\n",
"\n",
"f2 = f2.update_yaxes(\n",
" tickfont={'size':16},\n",
" tickformat = \"%Y-%m-%d\",\n",
" tick0 = '2024-11-15',\n",
" ticklabelstep=2,\n",
")"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Files Accessed"
]
},
{
"cell_type": "code",
"execution_count": 160,
"metadata": {},
"outputs": [],
"source": [
"accessed_no_churn = tld_agg.loc[(tld_agg['total_churn'].eq(0)) & (tld_agg['accessed'].gt(0))].index\n",
"accessed_no_churn_order = (\n",
" df\n",
" .loc[df['tld'].isin(accessed_no_churn)]\n",
" .groupby('tld',observed=True)['accessed']\n",
" .apply(lambda x: x.ne(0).sum())\n",
" .sort_values(ascending=False)\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 145,
"metadata": {},
"outputs": [],
"source": [
"accessed_order = order.to_list() + accessed_no_churn_order"
]
},
{
"cell_type": "code",
"execution_count": 146,
"metadata": {},
"outputs": [],
"source": [
"tick_text = [f'<span style=\"color:black\">{project}</span>' for project in order.to_list()] + \\\n",
" [f'<span style=\"color:red\">{project}</span>' for project in accessed_no_churn_order]"
]
},
{
"cell_type": "code",
"execution_count": 147,
"metadata": {},
"outputs": [],
"source": [
"accessed_df = df.loc[df['tld'].isin(accessed_order)]"
]
},
{
"cell_type": "code",
"execution_count": 153,
"metadata": {},
"outputs": [
{
"name": "stderr",
"output_type": "stream",
"text": [
"/home/mdefende/.conda/envs/gpfs/lib/python3.11/site-packages/pandas/core/arraylike.py:399: RuntimeWarning:\n",
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"f3 = go.Figure(\n",
" data = go.Heatmap(\n",
" z = np.log10(accessed_df['accessed']),\n",
" y = accessed_df['log_dt'],\n",
" x = accessed_df['tld'],\n",
" xgap=2,\n",
" colorscale=colorscale,\n",
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")"
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{
"cell_type": "code",
"execution_count": 158,
"metadata": {},
"outputs": [],
"source": [
"f3 = f3.update_layout(\n",
" template = 'plotly_white',\n",
" height = 1000,\n",
" width = 2200,\n",
" title = dict(\n",
" text = 'Time Course of Files Accessed But Not Churned For Projects Since 2024-11-14',\n",
" x = 0.5,\n",
" xanchor = 'center',\n",
" font_size = 30\n",
" ),\n",
"\n",
" xaxis = dict(\n",
" title = dict(\n",
" text = 'Directory Name',\n",
" font_size = 20\n",
" ),\n",
" gridwidth = 2,\n",
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" gridcolor='black',\n",
" categoryorder='array',\n",
" categoryarray=accessed_order,\n",
" tickvals=list(range(0,len(tick_text))),\n",
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" tickfont={'size':14},\n",
" ticklabelshift = 3,\n",
" tickson = 'boundaries'\n",
" ),\n",
" \n",
" yaxis = dict(\n",
" showgrid = False,\n",
" title = dict(\n",
" text = 'Policy Run Date',\n",
" font_size = 20\n",
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" gridcolor = 'black',\n",
" tickfont={'size':16},\n",
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")"
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},
{
"cell_type": "code",
"execution_count": 159,
"metadata": {},
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