{ "cells": [ { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### NXCALS and pyspark\n", "\n", "\n", "G. Sterbini with the help and support of the NXCALS team" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Introduction\n", "\n", "- We will present few examples on how to use **pyspark** methods to access NXCALS. \n", "\n", "- [pyspark](https://spark.apache.org/docs/latest/api/python/index.html) is a **ready-to-use package** supported by the Apache/SPARK community.\n", "\n", "- pyspark opens the possibility to make big data analysis and could be **complementary to pytimber**. \n", "\n", "Our aim here is to collect examples specific of our community and share them to optimize (and merge in future?) the different approaches.\n", "\n", "We are using the SWAN/NXCALS environment but we also tested the pyspark bundle and pure python approach (refer to [NXCALS web page](http://nxcals-docs.web.cern.ch/current/user-guide/data-access/access-methods/)).\n", "\n", "\n", "**We are NOT SPARK experts** but these examples (of incremental complexity) may bootstrap the discussion and help to build your own use-case.\n", "\n", "For our purpose, we privileged the clarity/compactness of code to the completeness of the physics case." ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### The logic\n", "Given a time window (two ordered timestamps) and a list of variables, one can follow 4 logic steps/sets of dataframes (**df**):\n", "1. Prepare a set of **single spark df's** (one per variable).\n", "2. **Join** this set in a **common spark df**.\n", "3. **Perform transformation** on the common spark df.\n", "4. **Retrieve a reduced spark df** converting it to **pandas df**.\n", "\n", "The emphasis is to do all transformation **before** step 4, hence make use of the NXCALS cluster.\n", "\n", "To keep in mind:\n", "\n", "- Working with the injectors data is in general easier (acquisition done by cyclestamp: **synchronous** acquisition due to strongly-coupled/fixed-duration-cycles/PPM-telegram).\n", "\n", "- Later we will show the more general case, e.g., LHC: **asynchronous** acquisition (weakly-coupled/no-fixed-duration-cycles/no-telegram)" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### An auxiliary package\n", "\n", "We put on https://github.com/sterbini/nx2pd (98 sloc) some recurrent functions we are going to use." ] }, { "cell_type": "code", "execution_count": 12, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [], "source": [ "import matplotlib \n", "matplotlib.rc('xtick', labelsize=20) \n", "matplotlib.rc('ytick', labelsize=20)\n", "from matplotlib import pyplot as plt\n", "plt.rcParams.update({'font.size': 22})\n", "from nx2pd import nx2pd as nx #install from https://github.com/sterbini/nx2pd\n", "nx.spark=spark\n", "pd=nx.pd\n", "np=nx.np" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 1a (no transformation)\n", "\n", "**Q: When and for which cycle a specific PS wire scanner was used?**\n", "\n", "In this example we are not making transformation (so we are not using the cluster in a smart way)." ] }, { "cell_type": "code", "execution_count": 3, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " CPS.LSA:CYCLE PR.BWS.65.H_ROT:SCAN_NUMBER\n", "2018-03-05 14:43:51.900000+00:00 EAST_IRRAD 46766\n", "2018-03-05 14:44:35.100000+00:00 EAST_IRRAD 46767\n", "2018-03-07 08:41:18.300000+00:00 EAST_IRRAD 46768\n", "2018-03-07 08:41:48.300000+00:00 EAST_IRRAD 46769\n", "2018-03-10 09:50:08.700000+00:00 MTE_50_CORE 46770\n", "A total of 15829 records retrieved.\n" ] } ], "source": [ "t1=pd.Timestamp('2018', tz='UTC')\n", "t2=pd.Timestamp('2019', tz='UTC')\n", "list_of_variables=['CPS.LSA:CYCLE','PR.BWS.65.H_ROT:SCAN_NUMBER']\n", "# Step 1: set of single spark df's\n", "pd_df_of_spark_df=nx.importNXCALS(list_of_variables, t1,t2)\n", "# Step 2: inner-joining the pd_df on 'timestamp'\n", "spark_df=nx._join_df_list(pd_df_of_spark_df, on=['timestamp'], how='inner')\n", "# Step 3: going back to pandas df\n", "# Nothing :(\n", "# Step 4: going back to pandas df\n", "pd_df=nx._to_pandas(spark_df, timestampConversion=True, sorted=True)\n", "print(pd_df.head());print(f'A total of {len(pd_df)} records retrieved.')" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 1b (with aggregation)\n", "\n", "**Q: Same question, when and for which cycle a specific PS wire scanner was used?**\n", "\n", "(now using aggregation)" ] }, { "cell_type": "code", "execution_count": 4, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " count\n", "MD4263_LHC25#48B_BCMS_PS_TFB_2018 2101\n", "MD4404_BCMS 1967\n", "MD2586_LHC25#12B_BCMS_PS 1684\n", "LHC25#48B_BCMS_PS 1064\n", "MD4407_LHC25#12B_BCMS 849\n", "A total of 108 records retrieved.\n" ] } ], "source": [ "t1=pd.Timestamp('2018', tz='UTC')\n", "t2=pd.Timestamp('2019', tz='UTC')\n", "list_of_variables=['CPS.LSA:CYCLE','PR.BWS.65.H_ROT:SCAN_NUMBER']\n", "# Step 1: set of single spark df's\n", "pd_df_of_spark_df=nx.importNXCALS(list_of_variables, t1,t2)\n", "# Step 2: inner-joining the pd_df on 'timestamp'\n", "spark_df=nx._join_df_list(pd_df_of_spark_df, on=['timestamp'], how='inner')\n", "# Step 3: aggregating the data\n", "spark_df=spark_df.groupby('CPS@LSA:CYCLE').agg(nx.func.count(\"PR@BWS@65@H_ROT:SCAN_NUMBER\").alias('count'))\n", "# Step 4: going back to pandas df\n", "pd_df=nx._to_pandas(spark_df,sorted=False).sort_values('count',ascending=False).set_index('CPS.LSA:CYCLE');pd_df.index.name=None;\n", "print(pd_df.head(5));print(f'A total of {len(pd_df)} records retrieved.')" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 2a (3 years aggregation)\n", "**Q: What is the statistics of the production cycles (first injection current) in the PS during Run2?**\n", "\n", "You can do that in less than 1 minutes in 2020/05/29 SWAN standard configuration!" ] }, { "cell_type": "code", "execution_count": 7, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " count sum(PR.DCAFTINJ_1:INTENSITY) avg(PR.DCAFTINJ_1:INTENSITY)\n", "TOF 7785564 5.312979e+09 682.414171\n", "SFTPRO1 2972325 3.270464e+09 1100.304861\n", "SFTPRO2 2242740 1.862863e+09 830.619392\n", "EAST1 3814038 1.044577e+09 273.876976\n", "EAST2 3677046 1.008520e+09 274.274491\n", "Total number of cycles: 54628119\n" ] } ], "source": [ "t1=pd.Timestamp('2016', tz='UTC'); t2=pd.Timestamp('2019', tz='UTC')\n", "pd_df=nx.importNXCALS(['CPS.TGM:USER','PR.DCAFTINJ_1:INTENSITY'], t1,t2)\n", "df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", "df=df.dropna()\\\n", " .groupby('CPS@TGM:USER').agg(nx.func.count(\"PR@DCAFTINJ_1:INTENSITY\").alias('count'),\\\n", " nx.func.sum(\"PR@DCAFTINJ_1:INTENSITY\"),\\\n", " nx.func.mean(\"PR@DCAFTINJ_1:INTENSITY\"))\n", "aux=nx._to_pandas(df)\n", "aux=aux.sort_values('CPS.TGM:USER').set_index('CPS.TGM:USER').sort_values('sum(PR.DCAFTINJ_1:INTENSITY)', ascending=False)\n", "aux.index.name=None;print(aux.head());print(f'Total number of cycles: {aux[\"count\"].sum()}')" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 2b (1 minute aggregation)\n", "**CAVEAT:** clearly it is faster but, as expected, there are overheads." ] }, { "cell_type": "code", "execution_count": 10, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " count sum mean std\n", "SFTPRO1 8 11461.413086 1432.676636 18.081495\n", "TOF 8 6481.819397 810.227425 9.617653\n", "EAST1 7 2806.542114 400.934588 2.437349\n", "EAST2 4 880.980518 220.245130 208.533554\n", "MD6 2 156.822815 78.411407 5.531555\n", "Total number of cycles: 35\n" ] } ], "source": [ "t1=pd.Timestamp('2018-10-01', tz='UTC'); t2=pd.Timestamp('2018-10-01 00:01', tz='UTC')\n", "pd_df=nx.importNXCALS(['CPS.TGM:USER','PR.DCAFTINJ_1:INTENSITY'], t1,t2)\n", "df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", "df=df.dropna()\\\n", " .groupby('CPS@TGM:USER').agg(nx.func.count(\"PR@DCAFTINJ_1:INTENSITY\").alias('count'),\\\n", " nx.func.sum(\"PR@DCAFTINJ_1:INTENSITY\").alias('sum'),\\\n", " nx.func.mean(\"PR@DCAFTINJ_1:INTENSITY\").alias('mean'),\\\n", " nx.func.stddev(\"PR@DCAFTINJ_1:INTENSITY\").alias('std'))\n", "aux=nx._to_pandas(df)\n", "aux=aux.sort_values('CPS.TGM:USER').set_index('CPS.TGM:USER').sort_values('sum', ascending=False)\n", "aux.index.name=None;print(aux.head());print(f'Total number of cycles: {aux[\"count\"].sum()}')" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 3 (daily cumulative aggregation)\n", "\n", "**Q: plot the integrated daily extracted current on PS TOF cycle for the 2018**\n", "\n", "We make explicit operation on the column 'timestamp' before aggregation and we use filtering." ] }, { "cell_type": "code", "execution_count": 11, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [], "source": [ "t1=pd.Timestamp('2018', tz='UTC')\n", "t2=pd.Timestamp('2019', tz='UTC')\n", "pd_df=nx.importNXCALS(['CPS.TGM:USER','PR.DCBEFEJE_1:INTENSITY'], t1,t2)\n", "df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", "df=df.filter(nx.col('CPS@TGM:USER')=='TOF')\n", "df=df.withColumn('new_timestamp',nx.col('timestamp')/1.0e9)\n", "df = df.withColumn('new_timestamp',nx.func.from_unixtime(\"new_timestamp\", \"yyyy-MM-dd HH:mm:ss\"))\n", "df_agg = df.groupBy(nx.func.to_date('new_timestamp').alias('Day')).agg(nx.func.sum('PR@DCBEFEJE_1:INTENSITY').alias('value'))\n", "# to pandas\n", "aux=nx._to_pandas(df_agg)\n", "# minimal operation in pandas after aggregation\n", "aux=aux.sort_values('Day').set_index('Day');aux.index.name=None" ] }, { "cell_type": "code", "execution_count": 13, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "image/png": 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\n", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(30,8))\n", "plt.plot(aux['value'].cumsum()/1e9,'-b')\n", "plt.title('Cumulative PR.DCBEFEJE_1:INTENSITY on TOF [1e19]')\n", "plt.xticks(rotation=20);\n", "plt.grid()" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 4 (cyclestamps arithmetic)\n", "\n", "**Q: What is the efficiency of transmission between PSB and PB for TOF?**\n", "\n", "Cyclestamps arithmetic can be used to \"follow\" a beam in the injector chain. \n", "\n", "**HINT**: \"consecutive\" cyclestamps from PS and PSB are 635 ms apart. " ] }, { "cell_type": "code", "execution_count": 19, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " CPS.TGM:USER PSB.TGM:USER efficiency\n", "1538352006700000000 TOF TOF 0.980367\n", "1538352010300000000 TOF TOF 0.977946\n", "1538352013900000000 TOF TOF 0.980870\n", "1538352028300000000 TOF TOF 0.979842\n", "1538352035500000000 TOF TOF 0.981096\n" ] } ], "source": [ "t1=pd.Timestamp('2018-10-01 00:00', tz='UTC')\n", "t2=pd.Timestamp('2018-10-01 00:05', tz='UTC')\n", "pd_df=nx.importNXCALS(['CPS.TGM:USER','PR.DCAFTINJ_1:INTENSITY'], t1,t2)\n", "df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", "df_ps=df.filter(nx.col('CPS@TGM:USER')=='TOF').filter(nx.col('PR@DCAFTINJ_1:INTENSITY')>500.)\n", "\n", "pd_df=nx.importNXCALS(['PSB.TGM:USER','BR2.BCT.ACC:INTENSITY'], t1,t2)\n", "df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", "df_psb=df.withColumn('timestamp',nx.col('timestamp')+635000000) # cyclestamps arithmetic\n", "\n", "out=nx._join_df_list([df_ps,df_psb],how='inner')\n", "out=out.withColumn('efficiency',nx.col('PR@DCAFTINJ_1:INTENSITY')/nx.col('BR2@BCT@ACC:INTENSITY'))\n", "print(nx._to_pandas(out, timestampConversion=False, sorted=True)[['CPS.TGM:USER','PSB.TGM:USER','efficiency']].head())" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 5 (UDF scalars to scalar)\n", "\n", "In the previous example we compute the efficiency just dividing columns. In general, for more complex, function we can use a User Defined Function. " ] }, { "cell_type": "code", "execution_count": 22, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " count Out/In PS efficiency\n", "AD 112549 0.988969\n", "EAST1 1166882 0.990395\n", "EAST2 1145499 0.992629\n", "ION1 53903 0.952219\n", "ION2 29311 0.793609\n" ] } ], "source": [ "# %% UDF scalars to scalar\n", "# This function compute the transmission efficiency between injection and extraction of the PS\n", "def my_efficiency(current_inj,current_eje):\n", " if current_inj>0:\n", " aux=current_eje/current_inj\n", " else:\n", " aux=0. # it is important to force the double for NXCALS\n", " if aux<0:\n", " return 0. # it is important to force the double for NXCALS\n", " else:\n", " return aux\n", "my_udf = nx.func.udf(my_efficiency, nx.DoubleType())\n", "\n", "t1=pd.Timestamp('2018', tz='UTC')\n", "t2=pd.Timestamp('2019', tz='UTC')\n", "pd_df=nx.importNXCALS(['CPS.TGM:USER','PR.DCAFTINJ_1:INTENSITY','PR.DCBEFEJE_1:INTENSITY'], t1,t2)\n", "spark_df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", "spark_df=spark_df.withColumn('transmission efficiency',my_udf(nx.col('PR@DCAFTINJ_1:INTENSITY'),nx.col('PR@DCBEFEJE_1:INTENSITY')))\n", "\n", "aux=nx._to_pandas(spark_df.dropna()\\\n", " .filter(nx.col(\"PR@DCAFTINJ_1:INTENSITY\")>2)\\\n", " .groupby('CPS@TGM:USER').agg(nx.func.count(\"transmission efficiency\").alias('count'),\\\n", " nx.func.mean(\"transmission efficiency\").alias('Out/In PS efficiency')))\n", "aux=aux.sort_values('CPS.TGM:USER').set_index('CPS.TGM:USER');aux.index.name=None;print(aux.head())" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 6 (UDF vector to scalar)\n", "**Q: Histogram of the multi-Turn Extraction efficiency in 2018**\n", "\n", "A natural extensions is to compress vector information to scalars." ] }, { "cell_type": "code", "execution_count": 23, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "data": { "image/png": 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "t1=pd.Timestamp('2018-10-01', tz='UTC')\n", "t2=pd.Timestamp('2018-10-01 00:01', tz='UTC')\n", "df=nx.importNXCALS(['CPS.TGM:USER','PR.SCOPE48.CH01:MTE_SPILL'], t1,t2)\n", "spark_df=nx._join_df_list(df, on=['timestamp'], how='inner')\n", "spark_df=spark_df.filter(nx.col('CPS@TGM:USER')=='SFTPRO1')\n", "plt.figure(figsize=(30,8))\n", "my_row=spark_df.take(2)[0]\n", "plt.plot(my_row['PR@SCOPE48@CH01:MTE_SPILL'],'b')\n", "plt.title(f'A typical MTE SPILL, {pd.Timestamp(my_row[\"timestamp\"]).tz_localize(\"UTC\")}') # it is a heavy signal (>20k samples)\n", "plt.xlabel('t [arb. units]');plt.ylabel('amplitude [arb. units]');plt.grid(True)" ] }, { "cell_type": "code", "execution_count": 24, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "+-------------------+------------+-------------+-------------------------+------------------------------+\n", "| timestamp|CPS@TGM:USER|CPS@LSA:CYCLE|PR@SCOPE48@CH01:MTE_SPILL|PR@SCOPE48@CH01:MTE_EFFICIENCY|\n", "+-------------------+------------+-------------+-------------------------+------------------------------+\n", "|1538352047500000000| SFTPRO1| MTE_2018_| [-124.17984259390...| 0.1969342292|\n", "|1538352046300000000| SFTPRO1| MTE_2018_| [160.132474568082...| 0.1974465434|\n", "|1538352003100000000| SFTPRO1| MTE_2018_| [-348.93102797674...| 0.1991091949|\n", "|1538352031900000000| SFTPRO1| MTE_2018_| [-127.18853975281...| 0.1994075732|\n", "|1538352004300000000| SFTPRO1| MTE_2018_| [241.22672082312,...| 0.1988264771|\n", "+-------------------+------------+-------------+-------------------------+------------------------------+\n", "\n" ] } ], "source": [ "t1=pd.Timestamp('2018-10-01', tz='UTC')\n", "t2=pd.Timestamp('2018-10-01 00:01', tz='UTC')\n", "df=nx.importNXCALS(['CPS.TGM:USER','CPS.LSA:CYCLE','PR.SCOPE48.CH01:MTE_SPILL','PR.SCOPE48.CH01:MTE_EFFICIENCY'], t1,t2)\n", "df=nx._join_df_list(df, on=['timestamp'], how='inner')\n", "df=df.filter(nx.col('CPS@TGM:USER')=='SFTPRO1')\n", "df.limit(5).show()" ] }, { "cell_type": "code", "execution_count": 29, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " PR.SCOPE48.CH01:MTE_EFFICIENCY recomputed\n", "2018-10-01 00:00:03.100000+00:00 0.199109 0.199109\n", "2018-10-01 00:00:04.300000+00:00 0.198826 0.198826\n", "2018-10-01 00:00:17.500000+00:00 0.198757 0.198757\n", "2018-10-01 00:00:18.700000+00:00 0.201958 0.201958\n", "2018-10-01 00:00:31.900000+00:00 0.199408 0.199408\n" ] } ], "source": [ "def MTE_efficiency(myNewSpill):\n", " b1_idx=2066-1500\n", " b2_idx=6267-1500\n", " b3_idx=10468-1500\n", " b4_idx=14669-1500\n", " b5_idx=18871-1500\n", " b6_idx=23072-1500\n", " is1=np.mean(myNewSpill[b1_idx:b2_idx])\n", " is2=np.mean(myNewSpill[b2_idx:b3_idx])\n", " is3=np.mean(myNewSpill[b3_idx:b4_idx])\n", " is4=np.mean(myNewSpill[b4_idx:b5_idx])\n", " core=np.mean(myNewSpill[b5_idx:b6_idx])\n", " mySum=(is1+is2+is3+is4+core);\n", " MTE_efficiency=np.mean([is1,is2,is3,is4])/mySum;\n", " return np.float(MTE_efficiency)\n", "my_udf = nx.func.udf(MTE_efficiency, nx.DoubleType())\n", "\n", "new_df=df.withColumn('recomputed',my_udf(nx.col('PR@SCOPE48@CH01:MTE_SPILL')))\n", "new_df=new_df.select(['timestamp','PR@SCOPE48@CH01:MTE_EFFICIENCY','recomputed'])\n", "print(nx._to_pandas(new_df, timestampConversion=True, sorted=True).head())" ] }, { "cell_type": "code", "execution_count": 30, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [], "source": [ "# about 5 minutes computation\n", "t1=pd.Timestamp('2018', tz='UTC')\n", "t2=pd.Timestamp('2019', tz='UTC')\n", "df=nx.importNXCALS(['CPS.TGM:USER','PR.SCOPE48.CH01:MTE_SPILL','PR.SCOPE48.CH01:MTE_EFFICIENCY'], t1,t2)\n", "df=nx._join_df_list(df, on=['timestamp'], how='inner')\n", "df=df.filter(nx.col('CPS@TGM:USER')=='SFTPRO1')\n", "new_df=df.withColumn('recomputed_MTE_efficiency',my_udf(nx.col('PR@SCOPE48@CH01:MTE_SPILL')))\n", "new_df=new_df.select(['recomputed_MTE_efficiency'])\n", "aux=nx._to_pandas(new_df)" ] }, { "cell_type": "code", "execution_count": 31, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "text/plain": [ "Text(0,0.5,'count')" ] }, "execution_count": 31, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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"text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "plt.figure(figsize=(30,8))\n", "aux=aux[(aux['recomputed_MTE_efficiency']>0) & (aux['recomputed_MTE_efficiency']<0.3)]\n", "plt.hist(aux['recomputed_MTE_efficiency'].values,1000);\n", "my_ylimit=plt.ylim()\n", "plt.plot([.2,.2],my_ylimit,'--r')\n", "plt.ylim(my_ylimit)\n", "plt.grid()\n", "plt.title('MTE splitting efficiency in 2018')\n", "plt.ylabel('count')" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 7 (subsampling and align scalars)\n", "\n", "We are going to put all together in our LHC case." ] }, { "cell_type": "code", "execution_count": 32, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [], "source": [ "def subSampling(variable,t1,t2,freq='300s'):\n", " aux=np.array(pd.date_range(t1, t2,freq=freq).astype(np.int64))\n", " spark_variable=nx._replace_specials(variable)\n", " pd_df=nx.importNXCALS([variable], t1,t2)\n", " def set_window(timestamp):\n", " try:\n", " return np.int(np.where(aux>timestamp)[0][0])\n", " except:\n", " return np.int(0)\n", " def set_window_time(window):\n", " try:\n", " return np.int((aux[window-1]+aux[window])/2)\n", " except:\n", " return np.int(0)\n", " udf_set_window = nx.func.udf(set_window, nx.LongType())\n", " udf_set_window_time = nx.func.udf(set_window_time, nx.LongType())\n", " spark_df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", " spark_df=spark_df.withColumn('window',udf_set_window(nx.col('timestamp')))\n", " spark_df=spark_df.withColumn('timeWindow',udf_set_window_time(nx.col('window')))\n", " return spark_df.groupby('window').agg(nx.func.mean(spark_variable).alias(spark_variable),\\\n", " nx.func.count(spark_variable).alias('count_'+spark_variable),\\\n", " nx.func.mean(spark_variable).alias('mean_'+spark_variable),\\\n", " nx.func.stddev(spark_variable).alias('stddev_'+spark_variable),\\\n", " nx.func.min(spark_variable).alias('min_'+spark_variable),\\\n", " nx.func.max(spark_variable).alias('max_'+spark_variable),\\\n", " nx.func.min(\"timeWindow\").alias(\"timestamp\")).drop('window')" ] }, { "cell_type": "code", "execution_count": 33, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " ALICE:LUMI_TOT_INST RPMBB.RR17.ROD.A12B1:I_MEAS\n", "2018-10-01 00:02:30+00:00 3.530905 -338.99\n", "2018-10-01 00:07:30+00:00 3.541737 -338.99\n", "2018-10-01 00:12:30+00:00 3.571198 -338.99\n", "2018-10-01 00:17:30+00:00 3.514797 -338.99\n", "2018-10-01 00:22:30+00:00 3.455339 -338.99\n" ] } ], "source": [ "t1=pd.Timestamp('2018-10-01', tz='UTC')\n", "t2=pd.Timestamp('2018-10-02', tz='UTC')\n", "my_variable_list=['ALICE:LUMI_TOT_INST','ATLAS:LUMI_TOT_INST','CMS:LUMI_TOT_INST','LHCB:LUMI_TOT_INST']\\\n", " +['LHC.BCTFR.A6R4.B1:BEAM_INTENSITY','LHC.BCTFR.A6R4.B2:BEAM_INTENSITY']\\\n", " +['LHC.BLM.LIFETIME:B1_BEAM_LIFETIME','LHC.BLM.LIFETIME:B2_BEAM_LIFETIME']+['RPMBB.RR17.ROD.A12B1:I_MEAS']\n", "my_spark_variable_list=nx._replace_specials(my_variable_list)\n", "my_list=[subSampling(i,t1,t2) for i in my_variable_list ]\n", "spark_df=nx._join_df_list(my_list, how='outer')\n", "aux=nx._to_pandas(spark_df.select(*my_spark_variable_list,'timestamp'), sorted=True, timestampConversion=True);print(aux[['ALICE:LUMI_TOT_INST','RPMBB.RR17.ROD.A12B1:I_MEAS']].head())" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 8 (putting together, subsampling and align vectors)\n", "\n", "To cope with bunch-by-bunch analysis we need to subsample vactors." ] }, { "cell_type": "code", "execution_count": 34, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [], "source": [ "def subSamplingVector(variable, t1, t2, my_DatetimeIndex):\n", " aux=np.array(my_DatetimeIndex.astype(np.int64))\n", " spark_variable=nx._replace_specials(variable)\n", " pd_df=nx.importNXCALS([variable], t1,t2)\n", " def set_window(timestamp):\n", " try:\n", " return np.int(np.where(aux>timestamp)[0][0])\n", " except:\n", " return np.int(0)\n", " def set_window_time(window):\n", " try:\n", " return np.int((aux[window-1]+aux[window])/2)\n", " #return np.int(aux[window-1])\n", " except:\n", " return np.int(0)\n", " def compute_mean(x):\n", " try:\n", " aux=0\n", " for i in len(x):\n", " aux=a+x[i]\n", " return aux/len(x)\n", " except:\n", " return x[0]\n", " udf_set_window = nx.func.udf(set_window, nx.LongType())\n", " udf_set_window_time = nx.func.udf(set_window_time, nx.LongType())\n", " udf_compute_mean = nx.func.udf(compute_mean, nx.ArrayType(nx.DoubleType()))\n", " spark_df=nx._join_df_list(pd_df, on=['timestamp'], how='inner')\n", " spark_df=spark_df.withColumn('window',udf_set_window(nx.col('timestamp')))\n", " spark_df=spark_df.withColumn('timeWindow',udf_set_window_time(nx.col('window')))\n", " return spark_df.groupby('window').agg(udf_compute_mean(nx.func.collect_list(spark_variable)).alias(spark_variable),\\\n", " nx.func.min(\"timeWindow\").alias(\"timestamp\")).drop('window')" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "subslide" } }, "source": [ "And combining the different functions..." ] }, { "cell_type": "code", "execution_count": 36, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " LHC.BSRT.5R4.B1:BUNCH_EMITTANCE_V \\\n", "2018-10-01 00:02:30+00:00 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "2018-10-01 00:07:30+00:00 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "2018-10-01 00:12:30+00:00 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "2018-10-01 00:14:20.149000+00:00 None \n", "2018-10-01 00:17:30+00:00 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ... \n", "\n", " LHC.RUNCONFIG:IP2-XING-V-MURAD \\\n", "2018-10-01 00:02:30+00:00 NaN \n", "2018-10-01 00:07:30+00:00 NaN \n", "2018-10-01 00:12:30+00:00 NaN \n", "2018-10-01 00:14:20.149000+00:00 NaN \n", "2018-10-01 00:17:30+00:00 NaN \n", "\n", " ATLAS:LUMI_TOT_INST \n", "2018-10-01 00:02:30+00:00 12800.725273 \n", "2018-10-01 00:07:30+00:00 12692.731878 \n", "2018-10-01 00:12:30+00:00 12588.781626 \n", "2018-10-01 00:14:20.149000+00:00 NaN \n", "2018-10-01 00:17:30+00:00 12518.875661 \n" ] } ], "source": [ "t1=pd.Timestamp('2018-10-01', tz='UTC')\n", "t2=pd.Timestamp('2018-10-02', tz='UTC')\n", "my_DatetimeIndex=pd.date_range(t1, t2, freq='300s')\n", "my_variable_list=['LHC.BCTFR.A6R4.B1:BUNCH_INTENSITY','LHC.BCTFR.A6R4.B2:BUNCH_INTENSITY','ATLAS:BUNCH_LUMI_INST','CMS:BUNCH_LUMI_INST',\n", " 'LHC.BSRT.5R4.B1:BUNCH_EMITTANCE_H',\n", " 'LHC.BSRT.5R4.B1:BUNCH_EMITTANCE_V',\n", " 'LHC.BSRT.5L4.B2:BUNCH_EMITTANCE_H',\n", " 'LHC.BSRT.5L4.B2:BUNCH_EMITTANCE_V']\n", "my_spark_variable_list=nx._replace_specials(my_variable_list)\n", "my_list1=[subSamplingVector(i,t1,t2,my_DatetimeIndex) for i in my_variable_list]\n", "\n", "my_variable_list=['ALICE:LUMI_TOT_INST','ATLAS:LUMI_TOT_INST','CMS:LUMI_TOT_INST','LHCB:LUMI_TOT_INST']\\\n", " +['LHC.BCTFR.A6R4.B1:BEAM_INTENSITY','LHC.BCTFR.A6R4.B2:BEAM_INTENSITY']\\\n", " +['LHC.BLM.LIFETIME:B1_BEAM_LIFETIME','LHC.BLM.LIFETIME:B2_BEAM_LIFETIME']+['RPMBB.RR17.ROD.A12B1:I_MEAS']\n", "my_spark_variable_list=nx._replace_specials(my_variable_list)\n", "my_list2=[subSampling(i,t1,t2) for i in my_variable_list ]\n", "\n", "my_list3=nx.importNXCALS(['LHC.RUNCONFIG:IP1-XING-V-MURAD',\n", " 'LHC.RUNCONFIG:IP2-XING-V-MURAD',\n", " 'LHC.RUNCONFIG:IP5-XING-H-MURAD',\n", " 'LHC.RUNCONFIG:IP8-XING-H-MURAD']+['HX:BETASTAR_IP1', 'HX:BETASTAR_IP2', 'HX:BETASTAR_IP5', 'HX:BETASTAR_IP8'], t1,t2)\n", "\n", "spark_df=nx._join_df_list(my_list1+my_list2+list(my_list3['pyspark df'].values), how='outer')\n", "aux=nx._to_pandas(spark_df, timestampConversion=True, sorted=True); print(aux[['LHC.BSRT.5R4.B1:BUNCH_EMITTANCE_V','LHC.RUNCONFIG:IP2-XING-V-MURAD','ATLAS:LUMI_TOT_INST']].head())" ] }, { "cell_type": "code", "execution_count": 37, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 37, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Few checks\n", "plt.figure(figsize=(30,8))\n", "plt.plot(aux.iloc[0]['LHC.BCTFR.A6R4.B1:BUNCH_INTENSITY'],'.-b', label='LHC.BCTFR.A6R4.B1:BUNCH_INTENSITY')\n", "plt.legend(loc='best')" ] }, { "cell_type": "code", "execution_count": 38, "metadata": { "slideshow": { "slide_type": "subslide" } }, "outputs": [ { "data": { "image/png": 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\n", "text/plain": [ "
" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "# Few checks\n", "plt.figure(figsize=(30,8))\n", "plt.plot(aux['LHC.BCTFR.A6R4.B2:BUNCH_INTENSITY'].dropna().apply(lambda x:x[6]),'.b-')\n", "plt.plot(aux['LHC.BCTFR.A6R4.B2:BUNCH_INTENSITY'].dropna().apply(lambda x:x[2000]),'.r-')\n", "plt.legend(loc='best')\n", "plt.grid()\n", "plt.xticks(rotation=20);" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Example 9 (write/read on HDFS)\n", "\n", "Writing and reading to/from HDFS allows us to use SPARK also for the postprocessed data (maintaining the same workflow)." ] }, { "cell_type": "code", "execution_count": 39, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [], "source": [ "# to write\n", "if 0:\n", " # very important to repartition to limit the number of files (for a single fill we will repartition to 1 file)\n", " spark_df.repartition(1).write.mode(\"overwrite\").parquet(\"fill2.parquet\")" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "fragment" } }, "source": [ "You can check the *hdfs* path by" ] }, { "cell_type": "code", "execution_count": 40, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Found 6 items\r\n", "drwx------ - sterbini supergroup 0 2020-05-28 23:20 /user/sterbini/.Trash\r\n", "drwxr-xr-x - sterbini supergroup 0 2020-05-29 10:31 /user/sterbini/.sparkStaging\r\n", "drwxr-xr-x - sterbini supergroup 0 2020-02-07 14:38 /user/sterbini/bmode\r\n", "drwxr-xr-x - sterbini supergroup 0 2020-02-07 14:51 /user/sterbini/bmodes\r\n", "drwxr-xr-x - sterbini supergroup 0 2020-05-28 22:40 /user/sterbini/fill1.parquet\r\n", "drwxr-xr-x - sterbini supergroup 0 2020-05-28 23:37 /user/sterbini/fill2.parquet\r\n" ] } ], "source": [ "!hdfs dfs -ls /user/sterbini" ] }, { "cell_type": "code", "execution_count": 48, "metadata": { "slideshow": { "slide_type": "fragment" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ " CMS:BUNCH_LUMI_INST\n", "2018-10-01 00:02:30+00:00 [-0.002677366, -0.002759958, -0.004399077, -0....\n", "2018-10-01 00:07:30+00:00 [-0.002629694, -0.002912038, -0.005541767, -0....\n", "2018-10-01 00:12:30+00:00 [-0.003120326, -0.002868722, -0.003427472, -0....\n", "2018-10-01 00:14:20.149000+00:00 None\n", "2018-10-01 00:17:30+00:00 [-0.001818355, -0.003197438, -0.002672729, -0....\n", " CMS:BUNCH_LUMI_INST\n", "2018-10-02 23:42:30+00:00 [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, ...\n", "2018-10-02 23:47:30+00:00 None\n", "2018-10-02 23:52:30+00:00 None\n", "2018-10-02 23:53:54.144000+00:00 None\n", "2018-10-02 23:57:30+00:00 None\n" ] } ], "source": [ "spark_df=spark.read.parquet(\"fill*.parquet\") # Very important\n", "aux=nx._to_pandas(spark_df.select('timestamp','CMS:BUNCH_LUMI_INST'),timestampConversion=True, sorted=True)\n", "print(aux.head())\n", "print(aux.tail())" ] }, { "cell_type": "markdown", "metadata": { "slideshow": { "slide_type": "slide" } }, "source": [ "### Conclusions\n", "\n", "- We show some examples of **pyspark** approach we intend to use in our work-flow. We touched only the surface. \n", "\n", "- First impression: we think that NXCALS framework has great potential for the big data analysis. \n", "\n", "- **pytimber** still fundamental for the typical use (e.g., small data).\n", "\n", "Thanks to the NXCALS team for the responsiveness and availability.\n", "\n", "**Thank you for your attention.**" ] } ], "metadata": { "celltoolbar": "Slideshow", "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.6.5" }, "sparkconnect": { "bundled_options": [ "NXCALS" ], "list_of_options": [] } }, "nbformat": 4, "nbformat_minor": 4 }