From fcfd2386e2ede9c005dd75e180ff2f802c3769b0 Mon Sep 17 00:00:00 2001 From: root Date: Sun, 19 Nov 2023 06:48:07 +0000 Subject: [PATCH] Removed old eda --- eda_2022_old.ipynb | 1808 -------------------------------------------- 1 file changed, 1808 deletions(-) delete mode 100644 eda_2022_old.ipynb diff --git a/eda_2022_old.ipynb b/eda_2022_old.ipynb deleted file mode 100644 index 31b29a3..0000000 --- a/eda_2022_old.ipynb +++ /dev/null @@ -1,1808 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "d417c7a9-4353-4914-a54c-75a596306449", - "metadata": {}, - "source": [ - "### EDA 2022\n", - "by Harsh Vardhan Pachisia" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "73eff743-b3c0-4fd5-8b14-02eb50abeae6", - "metadata": {}, - "outputs": [], - "source": [ - "from pyspark.sql import SparkSession\n", - "from pyspark.sql import functions as F\n", - "\n", - "import matplotlib.pyplot as plt\n", - "%matplotlib inline" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2d706dcc-35fe-43d5-bf08-80f8a75d4818", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - ":: loading settings :: url = jar:file:/usr/lib/spark/jars/ivy-2.5.1.jar!/org/apache/ivy/core/settings/ivysettings.xml\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Ivy Default Cache set to: /root/.ivy2/cache\n", - "The jars for the packages stored in: /root/.ivy2/jars\n", - "com.johnsnowlabs.nlp#spark-nlp_2.12 added as a dependency\n", - "graphframes#graphframes added as a dependency\n", - ":: resolving dependencies :: org.apache.spark#spark-submit-parent-59795f9d-11be-4787-8d1a-73a01beaeae5;1.0\n", - "\tconfs: [default]\n", - "\tfound com.johnsnowlabs.nlp#spark-nlp_2.12;4.4.0 in central\n", - "\tfound com.typesafe#config;1.4.2 in central\n", - "\tfound org.rocksdb#rocksdbjni;6.29.5 in central\n", - "\tfound com.amazonaws#aws-java-sdk-bundle;1.11.828 in central\n", - "\tfound com.github.universal-automata#liblevenshtein;3.0.0 in central\n", - "\tfound com.google.protobuf#protobuf-java-util;3.0.0-beta-3 in central\n", - "\tfound com.google.protobuf#protobuf-java;3.0.0-beta-3 in central\n", - "\tfound com.google.code.gson#gson;2.3 in central\n", - "\tfound it.unimi.dsi#fastutil;7.0.12 in central\n", - "\tfound org.projectlombok#lombok;1.16.8 in central\n", - "\tfound com.google.cloud#google-cloud-storage;2.16.0 in central\n", - "\tfound com.google.guava#guava;31.1-jre in central\n", - "\tfound com.google.guava#failureaccess;1.0.1 in central\n", - "\tfound com.google.guava#listenablefuture;9999.0-empty-to-avoid-conflict-with-guava in central\n", - "\tfound com.google.errorprone#error_prone_annotations;2.16 in central\n", - "\tfound com.google.j2objc#j2objc-annotations;1.3 in central\n", - "\tfound com.google.http-client#google-http-client;1.42.3 in central\n", - "\tfound io.opencensus#opencensus-contrib-http-util;0.31.1 in central\n", - "\tfound com.google.http-client#google-http-client-jackson2;1.42.3 in central\n", - "\tfound com.google.http-client#google-http-client-gson;1.42.3 in central\n", - "\tfound com.google.api-client#google-api-client;2.1.1 in central\n", - "\tfound commons-codec#commons-codec;1.15 in central\n", - "\tfound com.google.oauth-client#google-oauth-client;1.34.1 in central\n", - "\tfound com.google.http-client#google-http-client-apache-v2;1.42.3 in central\n", - "\tfound com.google.apis#google-api-services-storage;v1-rev20220705-2.0.0 in central\n", - "\tfound com.google.code.gson#gson;2.10 in central\n", - "\tfound com.google.cloud#google-cloud-core;2.9.0 in central\n", - "\tfound com.google.auto.value#auto-value-annotations;1.10.1 in central\n", - "\tfound com.google.cloud#google-cloud-core-http;2.9.0 in central\n", - "\tfound com.google.http-client#google-http-client-appengine;1.42.3 in central\n", - "\tfound com.google.api#gax-httpjson;0.105.1 in central\n", - "\tfound com.google.cloud#google-cloud-core-grpc;2.9.0 in central\n", - "\tfound io.grpc#grpc-core;1.51.0 in central\n", - "\tfound com.google.api#gax;2.20.1 in central\n", - "\tfound com.google.api#gax-grpc;2.20.1 in central\n", - "\tfound io.grpc#grpc-alts;1.51.0 in central\n", - "\tfound io.grpc#grpc-grpclb;1.51.0 in central\n", - "\tfound org.conscrypt#conscrypt-openjdk-uber;2.5.2 in central\n", - "\tfound io.grpc#grpc-protobuf;1.51.0 in central\n", - "\tfound com.google.auth#google-auth-library-credentials;1.13.0 in central\n", - "\tfound com.google.auth#google-auth-library-oauth2-http;1.13.0 in central\n", - "\tfound com.google.api#api-common;2.2.2 in central\n", - "\tfound javax.annotation#javax.annotation-api;1.3.2 in central\n", - "\tfound io.opencensus#opencensus-api;0.31.1 in central\n", - "\tfound io.grpc#grpc-context;1.51.0 in central\n", - "\tfound com.google.api.grpc#proto-google-iam-v1;1.6.22 in central\n", - "\tfound com.google.protobuf#protobuf-java;3.21.10 in central\n", - "\tfound com.google.protobuf#protobuf-java-util;3.21.10 in central\n", - "\tfound com.google.api.grpc#proto-google-common-protos;2.11.0 in central\n", - "\tfound org.threeten#threetenbp;1.6.4 in central\n", - "\tfound com.google.api.grpc#proto-google-cloud-storage-v2;2.16.0-alpha in central\n", - "\tfound com.google.api.grpc#grpc-google-cloud-storage-v2;2.16.0-alpha in central\n", - "\tfound com.google.api.grpc#gapic-google-cloud-storage-v2;2.16.0-alpha in central\n", - "\tfound com.fasterxml.jackson.core#jackson-core;2.14.1 in central\n", - "\tfound com.google.code.findbugs#jsr305;3.0.2 in central\n", - "\tfound io.grpc#grpc-api;1.51.0 in central\n", - "\tfound io.grpc#grpc-auth;1.51.0 in central\n", - "\tfound io.grpc#grpc-stub;1.51.0 in central\n", - "\tfound org.checkerframework#checker-qual;3.28.0 in central\n", - "\tfound com.google.api.grpc#grpc-google-iam-v1;1.6.22 in central\n", - "\tfound io.grpc#grpc-protobuf-lite;1.51.0 in central\n", - "\tfound com.google.android#annotations;4.1.1.4 in central\n", - "\tfound org.codehaus.mojo#animal-sniffer-annotations;1.22 in central\n", - "\tfound io.grpc#grpc-netty-shaded;1.51.0 in central\n", - "\tfound io.perfmark#perfmark-api;0.26.0 in central\n", - "\tfound io.grpc#grpc-googleapis;1.51.0 in central\n", - "\tfound io.grpc#grpc-xds;1.51.0 in central\n", - "\tfound io.opencensus#opencensus-proto;0.2.0 in central\n", - "\tfound io.grpc#grpc-services;1.51.0 in central\n", - "\tfound com.google.re2j#re2j;1.6 in central\n", - "\tfound com.navigamez#greex;1.0 in central\n", - "\tfound dk.brics.automaton#automaton;1.11-8 in central\n", - "\tfound com.johnsnowlabs.nlp#tensorflow-cpu_2.12;0.4.4 in central\n", - "\tfound graphframes#graphframes;0.8.2-spark3.1-s_2.12 in spark-packages\n", - "\tfound org.slf4j#slf4j-api;1.7.16 in central\n", - ":: resolution report :: resolve 1849ms :: artifacts dl 60ms\n", - "\t:: modules in use:\n", - "\tcom.amazonaws#aws-java-sdk-bundle;1.11.828 from central in [default]\n", - "\tcom.fasterxml.jackson.core#jackson-core;2.14.1 from central in [default]\n", - "\tcom.github.universal-automata#liblevenshtein;3.0.0 from central in [default]\n", - "\tcom.google.android#annotations;4.1.1.4 from central in [default]\n", - "\tcom.google.api#api-common;2.2.2 from central in [default]\n", - "\tcom.google.api#gax;2.20.1 from central in [default]\n", - "\tcom.google.api#gax-grpc;2.20.1 from central in [default]\n", - "\tcom.google.api#gax-httpjson;0.105.1 from central in [default]\n", - "\tcom.google.api-client#google-api-client;2.1.1 from central in [default]\n", - "\tcom.google.api.grpc#gapic-google-cloud-storage-v2;2.16.0-alpha from central in [default]\n", - "\tcom.google.api.grpc#grpc-google-cloud-storage-v2;2.16.0-alpha from central in [default]\n", - "\tcom.google.api.grpc#grpc-google-iam-v1;1.6.22 from central in [default]\n", - "\tcom.google.api.grpc#proto-google-cloud-storage-v2;2.16.0-alpha from central in [default]\n", - "\tcom.google.api.grpc#proto-google-common-protos;2.11.0 from central in [default]\n", - "\tcom.google.api.grpc#proto-google-iam-v1;1.6.22 from central in [default]\n", - "\tcom.google.apis#google-api-services-storage;v1-rev20220705-2.0.0 from central in [default]\n", - "\tcom.google.auth#google-auth-library-credentials;1.13.0 from central in [default]\n", - "\tcom.google.auth#google-auth-library-oauth2-http;1.13.0 from central in [default]\n", - "\tcom.google.auto.value#auto-value-annotations;1.10.1 from central in [default]\n", - "\tcom.google.cloud#google-cloud-core;2.9.0 from central in [default]\n", - "\tcom.google.cloud#google-cloud-core-grpc;2.9.0 from central in [default]\n", - "\tcom.google.cloud#google-cloud-core-http;2.9.0 from central in [default]\n", - "\tcom.google.cloud#google-cloud-storage;2.16.0 from central in [default]\n", - "\tcom.google.code.findbugs#jsr305;3.0.2 from central in [default]\n", - "\tcom.google.code.gson#gson;2.10 from central in [default]\n", - "\tcom.google.errorprone#error_prone_annotations;2.16 from central in [default]\n", - "\tcom.google.guava#failureaccess;1.0.1 from central in [default]\n", - "\tcom.google.guava#guava;31.1-jre from central in [default]\n", - "\tcom.google.guava#listenablefuture;9999.0-empty-to-avoid-conflict-with-guava from central in [default]\n", - "\tcom.google.http-client#google-http-client;1.42.3 from central in [default]\n", - "\tcom.google.http-client#google-http-client-apache-v2;1.42.3 from central in [default]\n", - "\tcom.google.http-client#google-http-client-appengine;1.42.3 from central in [default]\n", - "\tcom.google.http-client#google-http-client-gson;1.42.3 from central in [default]\n", - "\tcom.google.http-client#google-http-client-jackson2;1.42.3 from central in [default]\n", - "\tcom.google.j2objc#j2objc-annotations;1.3 from central in [default]\n", - "\tcom.google.oauth-client#google-oauth-client;1.34.1 from central in [default]\n", - "\tcom.google.protobuf#protobuf-java;3.21.10 from central in [default]\n", - "\tcom.google.protobuf#protobuf-java-util;3.21.10 from central in [default]\n", - "\tcom.google.re2j#re2j;1.6 from central in [default]\n", - "\tcom.johnsnowlabs.nlp#spark-nlp_2.12;4.4.0 from central in [default]\n", - "\tcom.johnsnowlabs.nlp#tensorflow-cpu_2.12;0.4.4 from central in [default]\n", - "\tcom.navigamez#greex;1.0 from central in [default]\n", - "\tcom.typesafe#config;1.4.2 from central in [default]\n", - "\tcommons-codec#commons-codec;1.15 from central in [default]\n", - "\tdk.brics.automaton#automaton;1.11-8 from central in [default]\n", - "\tgraphframes#graphframes;0.8.2-spark3.1-s_2.12 from spark-packages in [default]\n", - "\tio.grpc#grpc-alts;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-api;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-auth;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-context;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-core;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-googleapis;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-grpclb;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-netty-shaded;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-protobuf;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-protobuf-lite;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-services;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-stub;1.51.0 from central in [default]\n", - "\tio.grpc#grpc-xds;1.51.0 from central in [default]\n", - "\tio.opencensus#opencensus-api;0.31.1 from central in [default]\n", - "\tio.opencensus#opencensus-contrib-http-util;0.31.1 from central in [default]\n", - "\tio.opencensus#opencensus-proto;0.2.0 from central in [default]\n", - "\tio.perfmark#perfmark-api;0.26.0 from central in [default]\n", - "\tit.unimi.dsi#fastutil;7.0.12 from central in [default]\n", - "\tjavax.annotation#javax.annotation-api;1.3.2 from central in [default]\n", - "\torg.checkerframework#checker-qual;3.28.0 from central in [default]\n", - "\torg.codehaus.mojo#animal-sniffer-annotations;1.22 from central in [default]\n", - "\torg.conscrypt#conscrypt-openjdk-uber;2.5.2 from central in [default]\n", - "\torg.projectlombok#lombok;1.16.8 from central in [default]\n", - "\torg.rocksdb#rocksdbjni;6.29.5 from central in [default]\n", - "\torg.slf4j#slf4j-api;1.7.16 from central in [default]\n", - "\torg.threeten#threetenbp;1.6.4 from central in [default]\n", - "\t:: evicted modules:\n", - "\tcom.google.protobuf#protobuf-java-util;3.0.0-beta-3 by [com.google.protobuf#protobuf-java-util;3.21.10] in [default]\n", - "\tcom.google.protobuf#protobuf-java;3.0.0-beta-3 by [com.google.protobuf#protobuf-java;3.21.10] in [default]\n", - "\tcom.google.code.gson#gson;2.3 by [com.google.code.gson#gson;2.10] in [default]\n", - "\t---------------------------------------------------------------------\n", - "\t| | modules || artifacts |\n", - "\t| conf | number| search|dwnlded|evicted|| number|dwnlded|\n", - "\t---------------------------------------------------------------------\n", - "\t| default | 75 | 0 | 0 | 3 || 72 | 0 |\n", - "\t---------------------------------------------------------------------\n", - ":: retrieving :: org.apache.spark#spark-submit-parent-59795f9d-11be-4787-8d1a-73a01beaeae5\n", - "\tconfs: [default]\n", - "\t0 artifacts copied, 72 already retrieved (0kB/34ms)\n", - "Setting default log level to \"WARN\".\n", - "To adjust logging level use sc.setLogLevel(newLevel). For SparkR, use setLogLevel(newLevel).\n", - "23/11/16 00:54:56 INFO org.apache.spark.SparkEnv: Registering MapOutputTracker\n", - "23/11/16 00:54:56 INFO org.apache.spark.SparkEnv: Registering BlockManagerMaster\n", - "23/11/16 00:54:56 INFO org.apache.spark.SparkEnv: Registering BlockManagerMasterHeartbeat\n", - "23/11/16 00:54:57 INFO org.apache.spark.SparkEnv: Registering OutputCommitCoordinator\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.johnsnowlabs.nlp_spark-nlp_2.12-4.4.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/graphframes_graphframes-0.8.2-spark3.1-s_2.12.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.typesafe_config-1.4.2.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.rocksdb_rocksdbjni-6.29.5.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.amazonaws_aws-java-sdk-bundle-1.11.828.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.github.universal-automata_liblevenshtein-3.0.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.cloud_google-cloud-storage-2.16.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.navigamez_greex-1.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.johnsnowlabs.nlp_tensorflow-cpu_2.12-0.4.4.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/it.unimi.dsi_fastutil-7.0.12.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.projectlombok_lombok-1.16.8.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.guava_guava-31.1-jre.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.guava_failureaccess-1.0.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.guava_listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.errorprone_error_prone_annotations-2.16.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.j2objc_j2objc-annotations-1.3.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.http-client_google-http-client-1.42.3.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.opencensus_opencensus-contrib-http-util-0.31.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.http-client_google-http-client-jackson2-1.42.3.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.http-client_google-http-client-gson-1.42.3.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api-client_google-api-client-2.1.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/commons-codec_commons-codec-1.15.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.oauth-client_google-oauth-client-1.34.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.http-client_google-http-client-apache-v2-1.42.3.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.apis_google-api-services-storage-v1-rev20220705-2.0.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.code.gson_gson-2.10.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-2.9.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.auto.value_auto-value-annotations-1.10.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-http-2.9.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.http-client_google-http-client-appengine-1.42.3.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api_gax-httpjson-0.105.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-grpc-2.9.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-core-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api_gax-2.20.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api_gax-grpc-2.20.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-alts-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-grpclb-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.conscrypt_conscrypt-openjdk-uber-2.5.2.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-protobuf-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.auth_google-auth-library-credentials-1.13.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.auth_google-auth-library-oauth2-http-1.13.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api_api-common-2.2.2.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/javax.annotation_javax.annotation-api-1.3.2.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.opencensus_opencensus-api-0.31.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-context-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api.grpc_proto-google-iam-v1-1.6.22.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.protobuf_protobuf-java-3.21.10.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.protobuf_protobuf-java-util-3.21.10.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api.grpc_proto-google-common-protos-2.11.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.threeten_threetenbp-1.6.4.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api.grpc_proto-google-cloud-storage-v2-2.16.0-alpha.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api.grpc_grpc-google-cloud-storage-v2-2.16.0-alpha.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api.grpc_gapic-google-cloud-storage-v2-2.16.0-alpha.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.fasterxml.jackson.core_jackson-core-2.14.1.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.code.findbugs_jsr305-3.0.2.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-api-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-auth-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-stub-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.checkerframework_checker-qual-3.28.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.api.grpc_grpc-google-iam-v1-1.6.22.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-protobuf-lite-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.android_annotations-4.1.1.4.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.codehaus.mojo_animal-sniffer-annotations-1.22.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-netty-shaded-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.perfmark_perfmark-api-0.26.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-googleapis-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-xds-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.opencensus_opencensus-proto-0.2.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/io.grpc_grpc-services-1.51.0.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/com.google.re2j_re2j-1.6.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/dk.brics.automaton_automaton-1.11-8.jar added multiple times to distributed cache.\n", - "23/11/16 00:55:02 WARN org.apache.spark.deploy.yarn.Client: Same path resource file:///root/.ivy2/jars/org.slf4j_slf4j-api-1.7.16.jar added multiple times to distributed cache.\n" - ] - }, - { - "data": { - "text/plain": [ - "[('spark.stage.maxConsecutiveAttempts', '10'),\n", - " ('spark.dynamicAllocation.minExecutors', '1'),\n", - " ('spark.eventLog.enabled', 'true'),\n", - " ('spark.submit.pyFiles',\n", - " '/root/.ivy2/jars/com.johnsnowlabs.nlp_spark-nlp_2.12-4.4.0.jar,/root/.ivy2/jars/graphframes_graphframes-0.8.2-spark3.1-s_2.12.jar,/root/.ivy2/jars/com.typesafe_config-1.4.2.jar,/root/.ivy2/jars/org.rocksdb_rocksdbjni-6.29.5.jar,/root/.ivy2/jars/com.amazonaws_aws-java-sdk-bundle-1.11.828.jar,/root/.ivy2/jars/com.github.universal-automata_liblevenshtein-3.0.0.jar,/root/.ivy2/jars/com.google.cloud_google-cloud-storage-2.16.0.jar,/root/.ivy2/jars/com.navigamez_greex-1.0.jar,/root/.ivy2/jars/com.johnsnowlabs.nlp_tensorflow-cpu_2.12-0.4.4.jar,/root/.ivy2/jars/it.unimi.dsi_fastutil-7.0.12.jar,/root/.ivy2/jars/org.projectlombok_lombok-1.16.8.jar,/root/.ivy2/jars/com.google.guava_guava-31.1-jre.jar,/root/.ivy2/jars/com.google.guava_failureaccess-1.0.1.jar,/root/.ivy2/jars/com.google.guava_listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar,/root/.ivy2/jars/com.google.errorprone_error_prone_annotations-2.16.jar,/root/.ivy2/jars/com.google.j2objc_j2objc-annotations-1.3.jar,/root/.ivy2/jars/com.google.http-client_google-http-client-1.42.3.jar,/root/.ivy2/jars/io.opencensus_opencensus-contrib-http-util-0.31.1.jar,/root/.ivy2/jars/com.google.http-client_google-http-client-jackson2-1.42.3.jar,/root/.ivy2/jars/com.google.http-client_google-http-client-gson-1.42.3.jar,/root/.ivy2/jars/com.google.api-client_google-api-client-2.1.1.jar,/root/.ivy2/jars/commons-codec_commons-codec-1.15.jar,/root/.ivy2/jars/com.google.oauth-client_google-oauth-client-1.34.1.jar,/root/.ivy2/jars/com.google.http-client_google-http-client-apache-v2-1.42.3.jar,/root/.ivy2/jars/com.google.apis_google-api-services-storage-v1-rev20220705-2.0.0.jar,/root/.ivy2/jars/com.google.code.gson_gson-2.10.jar,/root/.ivy2/jars/com.google.cloud_google-cloud-core-2.9.0.jar,/root/.ivy2/jars/com.google.auto.value_auto-value-annotations-1.10.1.jar,/root/.ivy2/jars/com.google.cloud_google-cloud-core-http-2.9.0.jar,/root/.ivy2/jars/com.google.http-client_google-http-client-appengine-1.42.3.jar,/root/.ivy2/jars/com.google.api_gax-httpjson-0.105.1.jar,/root/.ivy2/jars/com.google.cloud_google-cloud-core-grpc-2.9.0.jar,/root/.ivy2/jars/io.grpc_grpc-core-1.51.0.jar,/root/.ivy2/jars/com.google.api_gax-2.20.1.jar,/root/.ivy2/jars/com.google.api_gax-grpc-2.20.1.jar,/root/.ivy2/jars/io.grpc_grpc-alts-1.51.0.jar,/root/.ivy2/jars/io.grpc_grpc-grpclb-1.51.0.jar,/root/.ivy2/jars/org.conscrypt_conscrypt-openjdk-uber-2.5.2.jar,/root/.ivy2/jars/io.grpc_grpc-protobuf-1.51.0.jar,/root/.ivy2/jars/com.google.auth_google-auth-library-credentials-1.13.0.jar,/root/.ivy2/jars/com.google.auth_google-auth-library-oauth2-http-1.13.0.jar,/root/.ivy2/jars/com.google.api_api-common-2.2.2.jar,/root/.ivy2/jars/javax.annotation_javax.annotation-api-1.3.2.jar,/root/.ivy2/jars/io.opencensus_opencensus-api-0.31.1.jar,/root/.ivy2/jars/io.grpc_grpc-context-1.51.0.jar,/root/.ivy2/jars/com.google.api.grpc_proto-google-iam-v1-1.6.22.jar,/root/.ivy2/jars/com.google.protobuf_protobuf-java-3.21.10.jar,/root/.ivy2/jars/com.google.protobuf_protobuf-java-util-3.21.10.jar,/root/.ivy2/jars/com.google.api.grpc_proto-google-common-protos-2.11.0.jar,/root/.ivy2/jars/org.threeten_threetenbp-1.6.4.jar,/root/.ivy2/jars/com.google.api.grpc_proto-google-cloud-storage-v2-2.16.0-alpha.jar,/root/.ivy2/jars/com.google.api.grpc_grpc-google-cloud-storage-v2-2.16.0-alpha.jar,/root/.ivy2/jars/com.google.api.grpc_gapic-google-cloud-storage-v2-2.16.0-alpha.jar,/root/.ivy2/jars/com.fasterxml.jackson.core_jackson-core-2.14.1.jar,/root/.ivy2/jars/com.google.code.findbugs_jsr305-3.0.2.jar,/root/.ivy2/jars/io.grpc_grpc-api-1.51.0.jar,/root/.ivy2/jars/io.grpc_grpc-auth-1.51.0.jar,/root/.ivy2/jars/io.grpc_grpc-stub-1.51.0.jar,/root/.ivy2/jars/org.checkerframework_checker-qual-3.28.0.jar,/root/.ivy2/jars/com.google.api.grpc_grpc-google-iam-v1-1.6.22.jar,/root/.ivy2/jars/io.grpc_grpc-protobuf-lite-1.51.0.jar,/root/.ivy2/jars/com.google.android_annotations-4.1.1.4.jar,/root/.ivy2/jars/org.codehaus.mojo_animal-sniffer-annotations-1.22.jar,/root/.ivy2/jars/io.grpc_grpc-netty-shaded-1.51.0.jar,/root/.ivy2/jars/io.perfmark_perfmark-api-0.26.0.jar,/root/.ivy2/jars/io.grpc_grpc-googleapis-1.51.0.jar,/root/.ivy2/jars/io.grpc_grpc-xds-1.51.0.jar,/root/.ivy2/jars/io.opencensus_opencensus-proto-0.2.0.jar,/root/.ivy2/jars/io.grpc_grpc-services-1.51.0.jar,/root/.ivy2/jars/com.google.re2j_re2j-1.6.jar,/root/.ivy2/jars/dk.brics.automaton_automaton-1.11-8.jar,/root/.ivy2/jars/org.slf4j_slf4j-api-1.7.16.jar'),\n", - " ('spark.dataproc.sql.joinConditionReorder.enabled', 'true'),\n", - " ('spark.app.startTime', '1700096096292'),\n", - " ('spark.kryoserializer.buffer.max', '2000M'),\n", - " ('spark.serializer', 'org.apache.spark.serializer.KryoSerializer'),\n", - " ('spark.dataproc.sql.local.rank.pushdown.enabled', 'true'),\n", - " ('spark.driver.maxResultSize', '0'),\n", - " ('spark.yarn.unmanagedAM.enabled', 'true'),\n", - " ('spark.sql.autoBroadcastJoinThreshold', '43m'),\n", - " ('spark.ui.filters',\n", - " 'org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter'),\n", - " ('spark.metrics.namespace',\n", - " 'app_name:${spark.app.name}.app_id:${spark.app.id}'),\n", - " ('spark.executor.memory', '4g'),\n", - " ('spark.dataproc.sql.optimizer.leftsemijoin.conversion.enabled', 'true'),\n", - " ('spark.hadoop.hive.execution.engine', 'mr'),\n", - " ('spark.executorEnv.PYTHONPATH',\n", - " 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'file:///root/.ivy2/jars/com.johnsnowlabs.nlp_spark-nlp_2.12-4.4.0.jar,file:///root/.ivy2/jars/graphframes_graphframes-0.8.2-spark3.1-s_2.12.jar,file:///root/.ivy2/jars/com.typesafe_config-1.4.2.jar,file:///root/.ivy2/jars/org.rocksdb_rocksdbjni-6.29.5.jar,file:///root/.ivy2/jars/com.amazonaws_aws-java-sdk-bundle-1.11.828.jar,file:///root/.ivy2/jars/com.github.universal-automata_liblevenshtein-3.0.0.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-storage-2.16.0.jar,file:///root/.ivy2/jars/com.navigamez_greex-1.0.jar,file:///root/.ivy2/jars/com.johnsnowlabs.nlp_tensorflow-cpu_2.12-0.4.4.jar,file:///root/.ivy2/jars/it.unimi.dsi_fastutil-7.0.12.jar,file:///root/.ivy2/jars/org.projectlombok_lombok-1.16.8.jar,file:///root/.ivy2/jars/com.google.guava_guava-31.1-jre.jar,file:///root/.ivy2/jars/com.google.guava_failureaccess-1.0.1.jar,file:///root/.ivy2/jars/com.google.guava_listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar,file:///root/.ivy2/jars/com.google.errorprone_error_prone_annotations-2.16.jar,file:///root/.ivy2/jars/com.google.j2objc_j2objc-annotations-1.3.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-1.42.3.jar,file:///root/.ivy2/jars/io.opencensus_opencensus-contrib-http-util-0.31.1.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-jackson2-1.42.3.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-gson-1.42.3.jar,file:///root/.ivy2/jars/com.google.api-client_google-api-client-2.1.1.jar,file:///root/.ivy2/jars/commons-codec_commons-codec-1.15.jar,file:///root/.ivy2/jars/com.google.oauth-client_google-oauth-client-1.34.1.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-apache-v2-1.42.3.jar,file:///root/.ivy2/jars/com.google.apis_google-api-services-storage-v1-rev20220705-2.0.0.jar,file:///root/.ivy2/jars/com.google.code.gson_gson-2.10.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-2.9.0.jar,file:///root/.ivy2/jars/com.google.auto.value_auto-value-annotations-1.10.1.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-http-2.9.0.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-appengine-1.42.3.jar,file:///root/.ivy2/jars/com.google.api_gax-httpjson-0.105.1.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-grpc-2.9.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-core-1.51.0.jar,file:///root/.ivy2/jars/com.google.api_gax-2.20.1.jar,file:///root/.ivy2/jars/com.google.api_gax-grpc-2.20.1.jar,file:///root/.ivy2/jars/io.grpc_grpc-alts-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-grpclb-1.51.0.jar,file:///root/.ivy2/jars/org.conscrypt_conscrypt-openjdk-uber-2.5.2.jar,file:///root/.ivy2/jars/io.grpc_grpc-protobuf-1.51.0.jar,file:///root/.ivy2/jars/com.google.auth_google-auth-library-credentials-1.13.0.jar,file:///root/.ivy2/jars/com.google.auth_google-auth-library-oauth2-http-1.13.0.jar,file:///root/.ivy2/jars/com.google.api_api-common-2.2.2.jar,file:///root/.ivy2/jars/javax.annotation_javax.annotation-api-1.3.2.jar,file:///root/.ivy2/jars/io.opencensus_opencensus-api-0.31.1.jar,file:///root/.ivy2/jars/io.grpc_grpc-context-1.51.0.jar,file:///root/.ivy2/jars/com.google.api.grpc_proto-google-iam-v1-1.6.22.jar,file:///root/.ivy2/jars/com.google.protobuf_protobuf-java-3.21.10.jar,file:///root/.ivy2/jars/com.google.protobuf_protobuf-java-util-3.21.10.jar,file:///root/.ivy2/jars/com.google.api.grpc_proto-google-common-protos-2.11.0.jar,file:///root/.ivy2/jars/org.threeten_threetenbp-1.6.4.jar,file:///root/.ivy2/jars/com.google.api.grpc_proto-google-cloud-storage-v2-2.16.0-alpha.jar,file:///root/.ivy2/jars/com.google.api.grpc_grpc-google-cloud-storage-v2-2.16.0-alpha.jar,file:///root/.ivy2/jars/com.google.api.grpc_gapic-google-cloud-storage-v2-2.16.0-alpha.jar,file:///root/.ivy2/jars/com.fasterxml.jackson.core_jackson-core-2.14.1.jar,file:///root/.ivy2/jars/com.google.code.findbugs_jsr305-3.0.2.jar,file:///root/.ivy2/jars/io.grpc_grpc-api-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-auth-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-stub-1.51.0.jar,file:///root/.ivy2/jars/org.checkerframework_checker-qual-3.28.0.jar,file:///root/.ivy2/jars/com.google.api.grpc_grpc-google-iam-v1-1.6.22.jar,file:///root/.ivy2/jars/io.grpc_grpc-protobuf-lite-1.51.0.jar,file:///root/.ivy2/jars/com.google.android_annotations-4.1.1.4.jar,file:///root/.ivy2/jars/org.codehaus.mojo_animal-sniffer-annotations-1.22.jar,file:///root/.ivy2/jars/io.grpc_grpc-netty-shaded-1.51.0.jar,file:///root/.ivy2/jars/io.perfmark_perfmark-api-0.26.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-googleapis-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-xds-1.51.0.jar,file:///root/.ivy2/jars/io.opencensus_opencensus-proto-0.2.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-services-1.51.0.jar,file:///root/.ivy2/jars/com.google.re2j_re2j-1.6.jar,file:///root/.ivy2/jars/dk.brics.automaton_automaton-1.11-8.jar,file:///root/.ivy2/jars/org.slf4j_slf4j-api-1.7.16.jar'),\n", - " ('spark.sql.cbo.enabled', 'true'),\n", - " ('spark.yarn.dist.jars',\n", - " 'file:///root/.ivy2/jars/com.johnsnowlabs.nlp_spark-nlp_2.12-4.4.0.jar,file:///root/.ivy2/jars/graphframes_graphframes-0.8.2-spark3.1-s_2.12.jar,file:///root/.ivy2/jars/com.typesafe_config-1.4.2.jar,file:///root/.ivy2/jars/org.rocksdb_rocksdbjni-6.29.5.jar,file:///root/.ivy2/jars/com.amazonaws_aws-java-sdk-bundle-1.11.828.jar,file:///root/.ivy2/jars/com.github.universal-automata_liblevenshtein-3.0.0.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-storage-2.16.0.jar,file:///root/.ivy2/jars/com.navigamez_greex-1.0.jar,file:///root/.ivy2/jars/com.johnsnowlabs.nlp_tensorflow-cpu_2.12-0.4.4.jar,file:///root/.ivy2/jars/it.unimi.dsi_fastutil-7.0.12.jar,file:///root/.ivy2/jars/org.projectlombok_lombok-1.16.8.jar,file:///root/.ivy2/jars/com.google.guava_guava-31.1-jre.jar,file:///root/.ivy2/jars/com.google.guava_failureaccess-1.0.1.jar,file:///root/.ivy2/jars/com.google.guava_listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar,file:///root/.ivy2/jars/com.google.errorprone_error_prone_annotations-2.16.jar,file:///root/.ivy2/jars/com.google.j2objc_j2objc-annotations-1.3.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-1.42.3.jar,file:///root/.ivy2/jars/io.opencensus_opencensus-contrib-http-util-0.31.1.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-jackson2-1.42.3.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-gson-1.42.3.jar,file:///root/.ivy2/jars/com.google.api-client_google-api-client-2.1.1.jar,file:///root/.ivy2/jars/commons-codec_commons-codec-1.15.jar,file:///root/.ivy2/jars/com.google.oauth-client_google-oauth-client-1.34.1.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-apache-v2-1.42.3.jar,file:///root/.ivy2/jars/com.google.apis_google-api-services-storage-v1-rev20220705-2.0.0.jar,file:///root/.ivy2/jars/com.google.code.gson_gson-2.10.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-2.9.0.jar,file:///root/.ivy2/jars/com.google.auto.value_auto-value-annotations-1.10.1.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-http-2.9.0.jar,file:///root/.ivy2/jars/com.google.http-client_google-http-client-appengine-1.42.3.jar,file:///root/.ivy2/jars/com.google.api_gax-httpjson-0.105.1.jar,file:///root/.ivy2/jars/com.google.cloud_google-cloud-core-grpc-2.9.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-core-1.51.0.jar,file:///root/.ivy2/jars/com.google.api_gax-2.20.1.jar,file:///root/.ivy2/jars/com.google.api_gax-grpc-2.20.1.jar,file:///root/.ivy2/jars/io.grpc_grpc-alts-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-grpclb-1.51.0.jar,file:///root/.ivy2/jars/org.conscrypt_conscrypt-openjdk-uber-2.5.2.jar,file:///root/.ivy2/jars/io.grpc_grpc-protobuf-1.51.0.jar,file:///root/.ivy2/jars/com.google.auth_google-auth-library-credentials-1.13.0.jar,file:///root/.ivy2/jars/com.google.auth_google-auth-library-oauth2-http-1.13.0.jar,file:///root/.ivy2/jars/com.google.api_api-common-2.2.2.jar,file:///root/.ivy2/jars/javax.annotation_javax.annotation-api-1.3.2.jar,file:///root/.ivy2/jars/io.opencensus_opencensus-api-0.31.1.jar,file:///root/.ivy2/jars/io.grpc_grpc-context-1.51.0.jar,file:///root/.ivy2/jars/com.google.api.grpc_proto-google-iam-v1-1.6.22.jar,file:///root/.ivy2/jars/com.google.protobuf_protobuf-java-3.21.10.jar,file:///root/.ivy2/jars/com.google.protobuf_protobuf-java-util-3.21.10.jar,file:///root/.ivy2/jars/com.google.api.grpc_proto-google-common-protos-2.11.0.jar,file:///root/.ivy2/jars/org.threeten_threetenbp-1.6.4.jar,file:///root/.ivy2/jars/com.google.api.grpc_proto-google-cloud-storage-v2-2.16.0-alpha.jar,file:///root/.ivy2/jars/com.google.api.grpc_grpc-google-cloud-storage-v2-2.16.0-alpha.jar,file:///root/.ivy2/jars/com.google.api.grpc_gapic-google-cloud-storage-v2-2.16.0-alpha.jar,file:///root/.ivy2/jars/com.fasterxml.jackson.core_jackson-core-2.14.1.jar,file:///root/.ivy2/jars/com.google.code.findbugs_jsr305-3.0.2.jar,file:///root/.ivy2/jars/io.grpc_grpc-api-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-auth-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-stub-1.51.0.jar,file:///root/.ivy2/jars/org.checkerframework_checker-qual-3.28.0.jar,file:///root/.ivy2/jars/com.google.api.grpc_grpc-google-iam-v1-1.6.22.jar,file:///root/.ivy2/jars/io.grpc_grpc-protobuf-lite-1.51.0.jar,file:///root/.ivy2/jars/com.google.android_annotations-4.1.1.4.jar,file:///root/.ivy2/jars/org.codehaus.mojo_animal-sniffer-annotations-1.22.jar,file:///root/.ivy2/jars/io.grpc_grpc-netty-shaded-1.51.0.jar,file:///root/.ivy2/jars/io.perfmark_perfmark-api-0.26.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-googleapis-1.51.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-xds-1.51.0.jar,file:///root/.ivy2/jars/io.opencensus_opencensus-proto-0.2.0.jar,file:///root/.ivy2/jars/io.grpc_grpc-services-1.51.0.jar,file:///root/.ivy2/jars/com.google.re2j_re2j-1.6.jar,file:///root/.ivy2/jars/dk.brics.automaton_automaton-1.11-8.jar,file:///root/.ivy2/jars/org.slf4j_slf4j-api-1.7.16.jar'),\n", - " ('spark.driver.host',\n", - " 'hub-msca-bdp-dphub-students-harshpachisia-m.c.msca-bdp-student-ap.internal'),\n", - " ('spark.dataproc.sql.parquet.enableFooterCache', 'true'),\n", - " ('spark.driver.memory', '4g'),\n", - " ('spark.sql.warehouse.dir', 'file:/spark-warehouse'),\n", - " ('spark.yarn.executor.failuresValidityInterval', '1h'),\n", - " ('spark.yarn.am.memory', '640m'),\n", - " ('spark.cores.max', '4'),\n", - " ('spark.executor.cores', '4'),\n", - " ('spark.history.fs.logDirectory',\n", - " 'gs://dataproc-temp-us-central1-635155370842-uzamlpgc/c51ecb68-26c8-4629-991b-7c7678561612/spark-job-history'),\n", - " ('spark.eventLog.dir',\n", - " 'gs://dataproc-temp-us-central1-635155370842-uzamlpgc/c51ecb68-26c8-4629-991b-7c7678561612/spark-job-history'),\n", - " ('spark.jars.packages',\n", - " 'com.johnsnowlabs.nlp:spark-nlp_2.12:4.4.0,graphframes:graphframes:0.8.2-spark3.1-s_2.12'),\n", - " ('spark.executor.instances', '2'),\n", - " ('spark.dataproc.listeners',\n", - " 'com.google.cloud.spark.performance.DataprocMetricsListener'),\n", - " ('spark.serializer.objectStreamReset', '100'),\n", - " ('spark.app.id', 'application_1700095878144_0002'),\n", - " ('spark.submit.deployMode', 'client'),\n", - " ('spark.org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter.param.PROXY_URI_BASES',\n", - " 'http://hub-msca-bdp-dphub-students-harshpachisia-m:8088/proxy/application_1700095878144_0002'),\n", - " ('spark.sql.cbo.joinReorder.enabled', 'true'),\n", - " ('spark.shuffle.service.enabled', 'true'),\n", - " ('spark.driver.port', '34413'),\n", - " ('spark.scheduler.mode', 'FAIR'),\n", - " ('spark.sql.adaptive.enabled', 'true'),\n", - " ('spark.yarn.jars', 'local:/usr/lib/spark/jars/*'),\n", - " ('spark.scheduler.minRegisteredResourcesRatio', '0.0'),\n", - " ('spark.driver.appUIAddress',\n", - " 'http://hub-msca-bdp-dphub-students-harshpachisia-m.c.msca-bdp-student-ap.internal:39235'),\n", - " ('spark.master', 'yarn'),\n", - " ('spark.ui.port', '0'),\n", - " ('spark.ui.proxyBase', '/proxy/application_1700095878144_0002'),\n", - " ('spark.rpc.message.maxSize', '512'),\n", - " ('spark.rdd.compress', 'True'),\n", - " ('spark.dataproc.metrics.listener.metrics.collector.hostname',\n", - " 'hub-msca-bdp-dphub-students-harshpachisia-m'),\n", - " ('spark.task.maxFailures', '10'),\n", - " ('spark.yarn.isPython', 'true'),\n", - " ('spark.dynamicAllocation.enabled', 'true'),\n", - " ('spark.ui.showConsoleProgress', 'true')]" - ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "spark = SparkSession.builder.appName('2022-EDA').getOrCreate()\n", - "\n", - "#change configuration settings on Spark \n", - "conf = spark.sparkContext._conf.setAll([('spark.executor.memory', '4g'), ('spark.app.name', 'Spark Updated Conf'), ('spark.executor.cores', '4'), ('spark.cores.max', '4'), ('spark.driver.memory','4g')])\n", - "\n", - "#print spark configuration settings\n", - "spark.sparkContext.getConf().getAll()" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "8a7c1334-5b9f-44d0-a66a-fc68e80226bc", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "root\n", - " |-- Trip ID: string (nullable = true)\n", - " |-- Trip Start Timestamp: string (nullable = true)\n", - " |-- Trip End Timestamp: string (nullable = true)\n", - " |-- Trip Seconds: integer (nullable = true)\n", - " |-- Trip Miles: double (nullable = true)\n", - " |-- Pickup Census Tract: long (nullable = true)\n", - " |-- Dropoff Census Tract: long (nullable = true)\n", - " |-- Pickup Community Area: integer (nullable = true)\n", - " |-- Dropoff Community Area: integer (nullable = true)\n", - " |-- Fare: double (nullable = true)\n", - " |-- Tip: integer (nullable = true)\n", - " |-- Additional Charges: double (nullable = true)\n", - " |-- Trip Total: double (nullable = true)\n", - " |-- Shared Trip Authorized: boolean (nullable = true)\n", - " |-- Trips Pooled: integer (nullable = true)\n", - " |-- Pickup Centroid Latitude: double (nullable = true)\n", - " |-- Pickup Centroid Longitude: double (nullable = true)\n", - " |-- Pickup Centroid Location: string (nullable = true)\n", - " |-- Dropoff Centroid Latitude: double (nullable = true)\n", - " |-- Dropoff Centroid Longitude: double (nullable = true)\n", - " |-- Dropoff Centroid Location: string (nullable = true)\n", - "\n", - "root\n", - " |-- name: string (nullable = true)\n", - " |-- datetime: string (nullable = true)\n", - " |-- tempmax: double (nullable = true)\n", - " |-- tempmin: double (nullable = true)\n", - " |-- temp: double (nullable = true)\n", - " |-- feelslikemax: double (nullable = true)\n", - " |-- feelslikemin: double (nullable = true)\n", - " |-- feelslike: double (nullable = true)\n", - " |-- dew: double (nullable = true)\n", - " |-- humidity: double (nullable = true)\n", - " |-- precip: double (nullable = true)\n", - " |-- precipprob: integer (nullable = true)\n", - " |-- precipcover: double (nullable = true)\n", - " |-- preciptype: string (nullable = true)\n", - " |-- snow: double (nullable = true)\n", - " |-- snowdepth: double (nullable = true)\n", - " |-- windgust: double (nullable = true)\n", - " |-- windspeed: double (nullable = true)\n", - " |-- winddir: double (nullable = true)\n", - " |-- sealevelpressure: double (nullable = true)\n", - " |-- cloudcover: double (nullable = true)\n", - " |-- visibility: double (nullable = true)\n", - " |-- solarradiation: double (nullable = true)\n", - " |-- solarenergy: double (nullable = true)\n", - " |-- uvindex: integer (nullable = true)\n", - " |-- severerisk: integer (nullable = true)\n", - " |-- sunrise: timestamp (nullable = true)\n", - " |-- sunset: timestamp (nullable = true)\n", - " |-- moonphase: double (nullable = true)\n", - " |-- conditions: string (nullable = true)\n", - " |-- description: string (nullable = true)\n", - " |-- icon: string (nullable = true)\n", - " |-- stations: string (nullable = true)\n", - "\n" - ] - } - ], - "source": [ - "df_2022 = spark.read.csv(\"gs://msca-bdp-student-gcs/bdp-rideshare-project/rideshare/2022\", inferSchema=True, header=True)\n", - "df_weather = spark.read.csv(\"gs://msca-bdp-student-gcs/bdp-rideshare-project/weather/chicago 2020-01-01 to 2022-08-31.csv\", inferSchema=True, header=True)\n", - "df_2022.printSchema()\n", - "df_weather.printSchema()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "97894943-6704-4759-8eba-df535e358995", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "135" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#display number of records by partition\n", - "def displaypartitions(df):\n", - " #number of records by partition\n", - " num = df.rdd.getNumPartitions()\n", - " print(\"Partitions:\", num)\n", - " df.withColumn(\"partitionId\", F.spark_partition_id())\\\n", - " .groupBy(\"partitionId\")\\\n", - " .count()\\\n", - " .orderBy(F.asc(\"count\"))\\\n", - " .show(num)\n", - "\n", - "df_2022.rdd.getNumPartitions()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "acfd7fd9-781b-4241-be03-a8ccd287ea0e", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Partitions: 135\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[Stage 4:======================================================>(134 + 1) / 135]\r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+-----------+------+\n", - "|partitionId| count|\n", - "+-----------+------+\n", - "| 134|337327|\n", - "| 22|499083|\n", - "| 123|504285|\n", - "| 126|504809|\n", - "| 115|504841|\n", - "| 95|505099|\n", - "| 87|505483|\n", - "| 10|505553|\n", - "| 129|505717|\n", - "| 109|505821|\n", - "| 30|506415|\n", - "| 12|506815|\n", - "| 112|506840|\n", - "| 118|506913|\n", - "| 8|507499|\n", - "| 17|507526|\n", - "| 40|507585|\n", - "| 53|507693|\n", - "| 90|507836|\n", - "| 27|507856|\n", - "| 71|508094|\n", - "| 100|508435|\n", - "| 103|508829|\n", - "| 74|508860|\n", - "| 92|509111|\n", - "| 106|509156|\n", - "| 50|509316|\n", - "| 45|509490|\n", - "| 25|509572|\n", - "| 79|509585|\n", - "| 48|509604|\n", - "| 89|509853|\n", - "| 32|510003|\n", - "| 66|510055|\n", - "| 58|510094|\n", - "| 82|510167|\n", - "| 37|510177|\n", - "| 61|510194|\n", - "| 6|510259|\n", - "| 35|510618|\n", - "| 19|510748|\n", - "| 4|510798|\n", - "| 68|510849|\n", - "| 77|510867|\n", - "| 97|511038|\n", - "| 98|511105|\n", - "| 15|511323|\n", - "| 5|511378|\n", - "| 94|511724|\n", - "| 42|512086|\n", - "| 3|512151|\n", - "| 47|512355|\n", - "| 84|512447|\n", - "| 24|512577|\n", - "| 128|512747|\n", - "| 14|512800|\n", - "| 76|512944|\n", - "| 102|513121|\n", - "| 56|513164|\n", - "| 69|513214|\n", - "| 33|513364|\n", - "| 63|513382|\n", - "| 101|513611|\n", - "| 117|513692|\n", - "| 55|513736|\n", - "| 104|513776|\n", - "| 1|513780|\n", - "| 20|513856|\n", - "| 21|513928|\n", - "| 29|513958|\n", - "| 122|514102|\n", - "| 51|514119|\n", - "| 60|514176|\n", - "| 28|514184|\n", - "| 125|514312|\n", - "| 13|514332|\n", - "| 105|514426|\n", - "| 73|514504|\n", - "| 81|514680|\n", - "| 88|514692|\n", - "| 108|514720|\n", - "| 64|514837|\n", - "| 114|514879|\n", - "| 43|514882|\n", - "| 38|514932|\n", - "| 16|514954|\n", - "| 91|514997|\n", - "| 39|515034|\n", - "| 130|515082|\n", - "| 7|515187|\n", - "| 57|515299|\n", - "| 107|515369|\n", - "| 70|515379|\n", - "| 52|515427|\n", - "| 2|515744|\n", - "| 86|515803|\n", - "| 49|516126|\n", - "| 127|516242|\n", - "| 85|516262|\n", - "| 54|516281|\n", - "| 116|516302|\n", - "| 111|516334|\n", - "| 44|516357|\n", - "| 93|516403|\n", - "| 65|516579|\n", - "| 110|516601|\n", - "| 34|516674|\n", - "| 23|516689|\n", - "| 67|516905|\n", - "| 124|516979|\n", - "| 133|517062|\n", - "| 96|517079|\n", - "| 72|517573|\n", - "| 36|517673|\n", - "| 26|517765|\n", - "| 99|517784|\n", - "| 41|517946|\n", - "| 9|518089|\n", - "| 113|518207|\n", - "| 83|518265|\n", - "| 0|518352|\n", - "| 78|518388|\n", - "| 46|518399|\n", - "| 121|518588|\n", - "| 11|518723|\n", - "| 75|518753|\n", - "| 31|518838|\n", - "| 59|518855|\n", - "| 80|518857|\n", - "| 18|519062|\n", - "| 131|519379|\n", - "| 62|519942|\n", - "| 119|521049|\n", - "| 120|521694|\n", - "| 132|527685|\n", - "+-----------+------+\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "displaypartitions(df_2022)" - ] - }, - { - "cell_type": "markdown", - "id": "266ec8da-9dc9-4db6-9cf3-e2f842756918", - "metadata": {}, - "source": [ - "Apart from partition ID 134- the rest of them seem to be fine. " - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "ce522e1b-1a6d-4c1f-bfb7-cdab74fa9758", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[Stage 7:===================================================> (7 + 1) / 8]\r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Partitions: 12\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[Stage 13:======================================> (141 + 8) / 200]\r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+-----------+------+\n", - "|partitionId| count|\n", - "+-----------+------+\n", - "| 11|308198|\n", - "| 2|308198|\n", - "| 1|308198|\n", - "| 0|308199|\n", - "| 9|308200|\n", - "| 10|308200|\n", - "| 7|308200|\n", - "| 3|308200|\n", - "| 4|308200|\n", - "| 6|308200|\n", - "| 8|308201|\n", - "| 5|308201|\n", - "+-----------+------+\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "#df_2022 = df_2022.repartition(12)\n", - "#displaypartitions(df_2022)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "449f3790-957a-4162-99da-c427b1f7f4f5", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+-------+--------------------+--------------------+--------------------+-----------------+-----------------+--------------------+--------------------+---------------------+----------------------+------------------+------------------+------------------+------------------+-------------------+------------------------+-------------------------+------------------------+-------------------------+--------------------------+-------------------------+\n", - "|summary| Trip ID|Trip Start Timestamp| Trip End Timestamp| Trip Seconds| Trip Miles| Pickup Census Tract|Dropoff Census Tract|Pickup Community Area|Dropoff Community Area| Fare| Tip|Additional Charges| Trip Total| Trips Pooled|Pickup Centroid Latitude|Pickup Centroid Longitude|Pickup Centroid Location|Dropoff Centroid Latitude|Dropoff Centroid Longitude|Dropoff Centroid Location|\n", - "+-------+--------------------+--------------------+--------------------+-----------------+-----------------+--------------------+--------------------+---------------------+----------------------+------------------+------------------+------------------+------------------+-------------------+------------------------+-------------------------+------------------------+-------------------------+--------------------------+-------------------------+\n", - "| count| 69109780| 69109780| 69109780| 69107640| 69109255| 39878136| 39743810| 63308104| 63060345| 68996153| 68996153| 68996153| 68996153| 69109780| 63504608| 63504608| 63504608| 63236931| 63236931| 63236931|\n", - "| mean| null| null| null|1087.989963685636|6.941177806069581|1.703138857357190...|1.703139982113558E10| 27.47473487754427| 28.182509198133946|18.581861223480097|1.2633003321214156| 4.695543582119797|24.540705137718618| 1.0103116085740687| 41.88968450848074| -87.67185807107674| null| 41.890209223177756| -87.67421914229088| null|\n", - "| stddev| null| null| null| 781.036239957131|7.794721602976051| 345215.07676459366| 349695.6602388101| 21.659446256851176| 22.084266814167|14.102800670263122| 2.923072207248932| 4.334114649952818|17.663201405445726|0.11431003790747415| 0.06748572087793586| 0.07044425727099544| null| 0.06719246755305787| 0.07502171489354009| null|\n", - "| min|0000000edc8f7b744...|01/01/2022 01:00:...|01/01/2022 01:00:...| 0| 0.0| 17031010100| 17031010100| 1| 1| 0.0| 0| 0.0| 0.0| 1| 41.6502216756| -87.913624596| POINT (-87.529950...| 41.6502216756| -87.913624596| POINT (-87.529950...|\n", - "| max|ffffffe6ece01c991...|12/31/2022 12:45:...|12/31/2022 12:45:...| 77556| 898.6| 17031980100| 17031980100| 77| 77| 1742.5| 200| 1658.84| 1767.45| 6| 42.0212235931| -87.529950466| POINT (-87.913624...| 42.0212235931| -87.529950466| POINT (-87.913624...|\n", - "+-------+--------------------+--------------------+--------------------+-----------------+-----------------+--------------------+--------------------+---------------------+----------------------+------------------+------------------+------------------+------------------+-------------------+------------------------+-------------------------+------------------------+-------------------------+--------------------------+-------------------------+\n", - "\n" - ] - } - ], - "source": [ - "df_2022.describe().show()" - ] - }, - { - "cell_type": "markdown", - "id": "0aff4005-3369-44cb-9b68-874dd43db0d1", - "metadata": {}, - "source": [ - "**Missing Values**" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "afcd9418-25d3-49a6-985a-3548a4040e49", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[Stage 4:======================================================>(133 + 2) / 135]\r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+-------+--------------------+------------------+------------+----------+-------------------+--------------------+---------------------+----------------------+------+------+------------------+----------+----------------------+------------+------------------------+-------------------------+------------------------+-------------------------+--------------------------+-------------------------+\n", - "|Trip ID|Trip Start Timestamp|Trip End Timestamp|Trip Seconds|Trip Miles|Pickup Census Tract|Dropoff Census Tract|Pickup Community Area|Dropoff Community Area| Fare| Tip|Additional Charges|Trip Total|Shared Trip Authorized|Trips Pooled|Pickup Centroid Latitude|Pickup Centroid Longitude|Pickup Centroid Location|Dropoff Centroid Latitude|Dropoff Centroid Longitude|Dropoff Centroid Location|\n", - "+-------+--------------------+------------------+------------+----------+-------------------+--------------------+---------------------+----------------------+------+------+------------------+----------+----------------------+------------+------------------------+-------------------------+------------------------+-------------------------+--------------------------+-------------------------+\n", - "| 0| 0| 0| 2140| 525| 29231644| 29365970| 5801676| 6049435|113627|113627| 113627| 113627| 0| 0| 5605172| 5605172| 5605172| 5872849| 5872849| 5872849|\n", - "+-------+--------------------+------------------+------------+----------+-------------------+--------------------+---------------------+----------------------+------+------+------------------+----------+----------------------+------------+------------------------+-------------------------+------------------------+-------------------------+--------------------------+-------------------------+\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "#Find the number of missing values for each column\n", - "from pyspark.sql.functions import isnan, when, count, col\n", - "# don't run for loops on the data, running for loops on the columns is fine, doing it on the entire data can cause problems. \n", - "df_2022.select([count(when(df_2022[c].isNull(), c)).alias(c) for c in df_2022.columns]).show()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "b3d609d2-6b4a-4b07-bd59-f1d796a65eeb", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import missingno as msno\n", - "%matplotlib inline\n", - "msno.matrix(df_2022.sample(fraction=1/10000).toPandas())" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "0289f522-acb2-4b40-aac8-c07ac28fea7c", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "text/plain": [ - "69109780" - ] - }, - "execution_count": 8, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "#number of trips in 2022\n", - "df_2022.distinct().count()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "d31bd799-7e96-406b-8c26-5874869efe50", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "text/plain": [ - "37047490" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# number of trips in 2022 without any na's\n", - "df_2022.dropna(how='any').count()" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "f2d52004-22fb-48ca-87f8-54377785f637", - "metadata": {}, - "outputs": [], - "source": [ - "df_2022 = df_2022.dropna(how='any')\n", - "df_2022 = df_2022.dropDuplicates()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "97d4446d-e4f8-485f-941b-f6b008def908", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "root\n", - " |-- Trip ID: string (nullable = true)\n", - " |-- Trip Start Timestamp: string (nullable = true)\n", - " |-- Trip End Timestamp: string (nullable = true)\n", - " |-- Trip Seconds: integer (nullable = true)\n", - " |-- Trip Miles: double (nullable = true)\n", - " |-- Pickup Census Tract: long (nullable = true)\n", - " |-- Dropoff Census Tract: long (nullable = true)\n", - " |-- Pickup Community Area: integer (nullable = true)\n", - " |-- Dropoff Community Area: integer (nullable = true)\n", - " |-- Fare: double (nullable = true)\n", - " |-- Tip: integer (nullable = true)\n", - " |-- Additional Charges: double (nullable = true)\n", - " |-- Trip Total: double (nullable = true)\n", - " |-- Shared Trip Authorized: boolean (nullable = true)\n", - " |-- Trips Pooled: integer (nullable = true)\n", - " |-- Pickup Centroid Latitude: double (nullable = true)\n", - " |-- Pickup Centroid Longitude: double (nullable = true)\n", - " |-- Pickup Centroid Location: string (nullable = true)\n", - " |-- Dropoff Centroid Latitude: double (nullable = true)\n", - " |-- Dropoff Centroid Longitude: double (nullable = true)\n", - " |-- Dropoff Centroid Location: string (nullable = true)\n", - "\n" - ] - } - ], - "source": [ - "df_2022.printSchema()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "ed13409a-88c3-4c28-9127-601534a8122a", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "[Stage 24:> (0 + 1) / 1]\r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+----------------------------------------+----------------------+----------------------+------------+----------+-------------------+--------------------+---------------------+----------------------+----+---+------------------+-----------------+----------------------+------------+------------------------+-------------------------+------------------------------------+-------------------------+--------------------------+------------------------------------+\n", - "|Trip ID |Trip Start Timestamp |Trip End Timestamp |Trip Seconds|Trip Miles|Pickup Census Tract|Dropoff Census Tract|Pickup Community Area|Dropoff Community Area|Fare|Tip|Additional Charges|Trip Total |Shared Trip Authorized|Trips Pooled|Pickup Centroid Latitude|Pickup Centroid Longitude|Pickup Centroid Location |Dropoff Centroid Latitude|Dropoff Centroid Longitude|Dropoff Centroid Location |\n", - "+----------------------------------------+----------------------+----------------------+------------+----------+-------------------+--------------------+---------------------+----------------------+----+---+------------------+-----------------+----------------------+------------+------------------------+-------------------------+------------------------------------+-------------------------+--------------------------+------------------------------------+\n", - "|8dfb4f4214fe066fc8a03ba5b51141fb33230389|01/01/2022 12:00:00 AM|01/01/2022 12:15:00 AM|789 |2.8 |17031320600 |17031243500 |32 |24 |10.0|5 |1.02 |16.02 |false |1 |41.8706073724 |-87.6221729369 |POINT (-87.6221729369 41.8706073724)|41.8926581076 |-87.6525344838 |POINT (-87.6525344838 41.8926581076)|\n", - "|93cc88a3584fcbf273550d5cd266fb49d943de94|01/01/2022 12:00:00 AM|01/01/2022 12:15:00 AM|267 |1.0 |17031062900 |17031070300 |6 |7 |5.0 |0 |2.36 |7.359999999999999|false |1 |41.9362371791 |-87.6564115308 |POINT (-87.6564115308 41.9362371791)|41.9290469366 |-87.6513108767 |POINT (-87.6513108767 41.9290469366)|\n", - "+----------------------------------------+----------------------+----------------------+------------+----------+-------------------+--------------------+---------------------+----------------------+----+---+------------------+-----------------+----------------------+------------+------------------------+-------------------------+------------------------------------+-------------------------+--------------------------+------------------------------------+\n", - "only showing top 2 rows\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "df_2022.show(2, truncate = False)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "24bebb17-1429-4ee6-b154-15a467f7160e", - "metadata": {}, - "outputs": [], - "source": [ - "# Convert 'Trip start timestamp' and 'Trip End Timestamp' columns to timestamp\n", - "df_2022 = df_2022.withColumn(\"Trip Start Timestamp\", F.to_timestamp(F.col(\"Trip Start Timestamp\"), \"MM/dd/yyyy hh:mm:ss a\"))\n", - "df_2022 = df_2022.withColumn(\"Trip End Timestamp\", F.to_timestamp(F.col(\"Trip End Timestamp\"), \"MM/dd/yyyy hh:mm:ss a\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "4bca707f-6353-4d1d-8241-fcaddc5bf515", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "root\n", - " |-- Trip ID: string (nullable = true)\n", - " |-- Trip Start Timestamp: timestamp (nullable = true)\n", - " |-- Trip End Timestamp: timestamp (nullable = true)\n", - " |-- Trip Seconds: integer (nullable = true)\n", - " |-- Trip Miles: double (nullable = true)\n", - " |-- Pickup Census Tract: long (nullable = true)\n", - " |-- Dropoff Census Tract: long (nullable = true)\n", - " |-- Pickup Community Area: integer (nullable = true)\n", - " |-- Dropoff Community Area: integer (nullable = true)\n", - " |-- Fare: double (nullable = true)\n", - " |-- Tip: integer (nullable = true)\n", - " |-- Additional Charges: double (nullable = true)\n", - " |-- Trip Total: double (nullable = true)\n", - " |-- Shared Trip Authorized: boolean (nullable = true)\n", - " |-- Trips Pooled: integer (nullable = true)\n", - " |-- Pickup Centroid Latitude: double (nullable = true)\n", - " |-- Pickup Centroid Longitude: double (nullable = true)\n", - " |-- Pickup Centroid Location: string (nullable = true)\n", - " |-- Dropoff Centroid Latitude: double (nullable = true)\n", - " |-- Dropoff Centroid Longitude: double (nullable = true)\n", - " |-- Dropoff Centroid Location: string (nullable = true)\n", - "\n" - ] - } - ], - "source": [ - "df_2022.printSchema()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "85685901-9312-40e7-a54a-df17127fbfa0", - "metadata": {}, - "outputs": [], - "source": [ - "df_2022 = df_2022.drop('Trips Pooled','Additional Charges','Shared Trip Authorized', \"Tip\")\n", - "df_2022 = df_2022.withColumnRenamed(\"Trip ID\",\"ID\").withColumnRenamed(\"Trip Start Timestamp\",\"start_timestamp\").withColumnRenamed(\"Trip End Timestamp\",\"end_timestamp\").withColumnRenamed(\"Trip Miles\",\\\n", - " \"miles\").withColumnRenamed(\"Pickup Census Tract\",\"pickup_tract\").withColumnRenamed(\"Dropoff Census Tract\",\"dropoff_tract\").withColumnRenamed(\"Pickup Community Area\",\"pickup_area\"\\\n", - " ).withColumnRenamed(\"Dropoff Community Area\",\"dropoff_area\").withColumnRenamed(\"Trip Total\",\"total\").withColumnRenamed(\"Pickup Centroid Latitude\",\"pickup_lat\").withColumnRenamed(\\\n", - " \"Pickup Centroid Longitude\",\"pickup_lon\").withColumnRenamed(\"Pickup Centroid Location\",\"pickup_location\").withColumnRenamed(\"Dropoff Centroid Latitude\",\"dropoff_lat\").withColumnRenamed(\\\n", - " \"Dropoff Centroid Longitude\",\"dropoff_lon\").withColumnRenamed(\"Dropoff Centroid Latitude\", \"dropoff_lat\").withColumnRenamed(\"Trip Seconds\", \"trip_seconds\").withColumnRenamed(\"Dropoff Centroid Location\", \"dropoff_location\").withColumnRenamed(\"Fare\", \"fare\")" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "0f1c8e0d-ce51-46b7-9cae-bc78b96f92f0", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "root\n", - " |-- ID: string (nullable = true)\n", - " |-- start_timestamp: timestamp (nullable = true)\n", - " |-- end_timestamp: timestamp (nullable = true)\n", - " |-- trip_seconds: integer (nullable = true)\n", - " |-- miles: double (nullable = true)\n", - " |-- pickup_tract: long (nullable = true)\n", - " |-- dropoff_tract: long (nullable = true)\n", - " |-- pickup_area: integer (nullable = true)\n", - " |-- dropoff_area: integer (nullable = true)\n", - " |-- fare: double (nullable = true)\n", - " |-- total: double (nullable = true)\n", - " |-- pickup_lat: double (nullable = true)\n", - " |-- pickup_lon: double (nullable = true)\n", - " |-- pickup_location: string (nullable = true)\n", - " |-- dropoff_lat: double (nullable = true)\n", - " |-- dropoff_lon: double (nullable = true)\n", - " |-- dropoff_location: string (nullable = true)\n", - "\n" - ] - } - ], - "source": [ - "df_2022.printSchema()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "9139d754-51a7-4f27-985c-a48a29772260", - "metadata": {}, - "outputs": [], - "source": [ - "df_weather = df_weather.withColumn('datetime',F.to_date(df_weather['datetime'], \"yyyy-mm-dd\"))" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "a4a63991-14f6-4f0d-84d2-4529e35dac56", - "metadata": {}, - "outputs": [], - "source": [ - "df_2022 = df_2022.withColumn('date_only', F.to_date(df_2022.end_timestamp))\n", - "#df_2022.select('end_timestamp').distinct().show(10)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "bafd9dcc-1c52-43e6-86f5-76f0ea4bd962", - "metadata": {}, - "outputs": [], - "source": [ - "# add the month column\n", - "df_2022 = df_2022.withColumn('month', F.month(df_2022.start_timestamp))\n", - "df_2022 = df_2022.withColumn('hour', F.hour(df_2022.start_timestamp))" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "c59a3717-82ba-4d35-b6ec-3ab40b31ae3d", - "metadata": {}, - "outputs": [], - "source": [ - "# get rides that occurred within hyde park\n", - "# add kenwood and woodlawn to this list - only if the other location is hyde park \n", - "df_hp = df_2022.filter((df_2022.pickup_area == 41) & (df_2022.dropoff_area == 41))\n", - "df_kw = df_2022.filter(((df_2022.pickup_area == 41) & (df_2022.dropoff_area == 42)) | ((df_2022.pickup_area == 42) & (df_2022.dropoff_area == 41)))\n", - "df_wl = df_2022.filter(((df_2022.pickup_area == 41) & (df_2022.dropoff_area == 39)) | ((df_2022.pickup_area == 39) & (df_2022.dropoff_area == 41)))\n", - "df_area = df_hp.union(df_kw).union(df_wl)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "eb76b842-07b3-4488-9cdb-bd382a8afc4c", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+--------------------+-------------------+-------------------+------------+-----+------------+-------------+-----------+------------+----+-----+------------+-------------+--------------------+------------+-------------+--------------------+----------+-----+----+\n", - "| ID| start_timestamp| end_timestamp|trip_seconds|miles|pickup_tract|dropoff_tract|pickup_area|dropoff_area|fare|total| pickup_lat| pickup_lon| pickup_location| dropoff_lat| dropoff_lon| dropoff_location| date_only|month|hour|\n", - "+--------------------+-------------------+-------------------+------------+-----+------------+-------------+-----------+------------+----+-----+------------+-------------+--------------------+------------+-------------+--------------------+----------+-----+----+\n", - "|2e4b382f14613d0eb...|2022-01-01 00:00:00|2022-01-01 00:00:00| 263| 1.1| null| null| 41| 41| 5.0| 7.58|41.794090253|-87.592310855|POINT (-87.592310...|41.794090253|-87.592310855|POINT (-87.592310...|2022-01-01| 1| 0|\n", - "|87fff1174eab85106...|2022-01-01 00:00:00|2022-01-01 00:15:00| 290| 0.8| null| null| 41| 41|10.0|11.02|41.794090253|-87.592310855|POINT (-87.592310...|41.794090253|-87.592310855|POINT (-87.592310...|2022-01-01| 1| 0|\n", - "|f2bb10941e2f09c3d...|2022-01-01 00:00:00|2022-01-01 00:00:00| 162| 0.6| null| null| 41| 41|10.0|11.02|41.794090253|-87.592310855|POINT (-87.592310...|41.794090253|-87.592310855|POINT (-87.592310...|2022-01-01| 1| 0|\n", - "|276dba10afcca6d89...|2022-01-01 00:15:00|2022-01-01 00:15:00| 133| 0.5| null| null| 41| 41|15.0|16.02|41.794090253|-87.592310855|POINT (-87.592310...|41.794090253|-87.592310855|POINT (-87.592310...|2022-01-01| 1| 0|\n", - "|a03c726943e77be10...|2022-01-01 00:15:00|2022-01-01 00:15:00| 228| 1.2| null| null| 41| 41|20.0|21.02|41.794090253|-87.592310855|POINT (-87.592310...|41.794090253|-87.592310855|POINT (-87.592310...|2022-01-01| 1| 0|\n", - "+--------------------+-------------------+-------------------+------------+-----+------------+-------------+-----------+------------+----+-----+------------+-------------+--------------------+------------+-------------+--------------------+----------+-----+----+\n", - "only showing top 5 rows\n", - "\n" - ] - } - ], - "source": [ - "df_area.show(5)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "3eace256-7c8d-4501-96ee-5deb9b5411c2", - "metadata": {}, - "outputs": [ - { - "ename": "AnalysisException", - "evalue": "path gs://msca-bdp-student-gcs/bdp-rideshare-project/rideshare/processed_data/2022 already exists.", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAnalysisException\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[32], line 2\u001b[0m\n\u001b[1;32m 1\u001b[0m \u001b[38;5;66;03m# storing data on the bucket\u001b[39;00m\n\u001b[0;32m----> 2\u001b[0m \u001b[43mdf_area\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwrite\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43moption\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mheader\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mtrue\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcsv\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mgs://msca-bdp-student-gcs/bdp-rideshare-project/rideshare/processed_data/2022\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/usr/lib/spark/python/pyspark/sql/readwriter.py:1372\u001b[0m, in \u001b[0;36mDataFrameWriter.csv\u001b[0;34m(self, path, mode, compression, sep, quote, escape, header, nullValue, escapeQuotes, quoteAll, dateFormat, timestampFormat, ignoreLeadingWhiteSpace, ignoreTrailingWhiteSpace, charToEscapeQuoteEscaping, encoding, emptyValue, lineSep)\u001b[0m\n\u001b[1;32m 1364\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mmode(mode)\n\u001b[1;32m 1365\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_set_opts(compression\u001b[38;5;241m=\u001b[39mcompression, sep\u001b[38;5;241m=\u001b[39msep, quote\u001b[38;5;241m=\u001b[39mquote, escape\u001b[38;5;241m=\u001b[39mescape, header\u001b[38;5;241m=\u001b[39mheader,\n\u001b[1;32m 1366\u001b[0m nullValue\u001b[38;5;241m=\u001b[39mnullValue, escapeQuotes\u001b[38;5;241m=\u001b[39mescapeQuotes, quoteAll\u001b[38;5;241m=\u001b[39mquoteAll,\n\u001b[1;32m 1367\u001b[0m dateFormat\u001b[38;5;241m=\u001b[39mdateFormat, timestampFormat\u001b[38;5;241m=\u001b[39mtimestampFormat,\n\u001b[0;32m (...)\u001b[0m\n\u001b[1;32m 1370\u001b[0m charToEscapeQuoteEscaping\u001b[38;5;241m=\u001b[39mcharToEscapeQuoteEscaping,\n\u001b[1;32m 1371\u001b[0m encoding\u001b[38;5;241m=\u001b[39mencoding, emptyValue\u001b[38;5;241m=\u001b[39memptyValue, lineSep\u001b[38;5;241m=\u001b[39mlineSep)\n\u001b[0;32m-> 1372\u001b[0m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_jwrite\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcsv\u001b[49m\u001b[43m(\u001b[49m\u001b[43mpath\u001b[49m\u001b[43m)\u001b[49m\n", - "File \u001b[0;32m/opt/conda/miniconda3/lib/python3.8/site-packages/py4j/java_gateway.py:1304\u001b[0m, in \u001b[0;36mJavaMember.__call__\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m 1298\u001b[0m command \u001b[38;5;241m=\u001b[39m proto\u001b[38;5;241m.\u001b[39mCALL_COMMAND_NAME \u001b[38;5;241m+\u001b[39m\\\n\u001b[1;32m 1299\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcommand_header \u001b[38;5;241m+\u001b[39m\\\n\u001b[1;32m 1300\u001b[0m args_command \u001b[38;5;241m+\u001b[39m\\\n\u001b[1;32m 1301\u001b[0m proto\u001b[38;5;241m.\u001b[39mEND_COMMAND_PART\n\u001b[1;32m 1303\u001b[0m answer \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mgateway_client\u001b[38;5;241m.\u001b[39msend_command(command)\n\u001b[0;32m-> 1304\u001b[0m return_value \u001b[38;5;241m=\u001b[39m \u001b[43mget_return_value\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m 1305\u001b[0m \u001b[43m \u001b[49m\u001b[43manswer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mgateway_client\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mtarget_id\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mname\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 1307\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m temp_arg \u001b[38;5;129;01min\u001b[39;00m temp_args:\n\u001b[1;32m 1308\u001b[0m temp_arg\u001b[38;5;241m.\u001b[39m_detach()\n", - "File \u001b[0;32m/usr/lib/spark/python/pyspark/sql/utils.py:117\u001b[0m, in \u001b[0;36mcapture_sql_exception..deco\u001b[0;34m(*a, **kw)\u001b[0m\n\u001b[1;32m 113\u001b[0m converted \u001b[38;5;241m=\u001b[39m convert_exception(e\u001b[38;5;241m.\u001b[39mjava_exception)\n\u001b[1;32m 114\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(converted, UnknownException):\n\u001b[1;32m 115\u001b[0m \u001b[38;5;66;03m# Hide where the exception came from that shows a non-Pythonic\u001b[39;00m\n\u001b[1;32m 116\u001b[0m \u001b[38;5;66;03m# JVM exception message.\u001b[39;00m\n\u001b[0;32m--> 117\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m converted \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m\n\u001b[1;32m 118\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m 119\u001b[0m \u001b[38;5;28;01mraise\u001b[39;00m\n", - "\u001b[0;31mAnalysisException\u001b[0m: path gs://msca-bdp-student-gcs/bdp-rideshare-project/rideshare/processed_data/2022 already exists." - ] - } - ], - "source": [] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "26002433-fed0-47d4-a73b-54f4b9deed1c", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 14, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "df_area.groupby(\"month\").agg({'ID':'count'}).orderBy(F.col('month').asc()).toPandas().plot(x=\"month\",y=\"count(ID)\")" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "1e554be2-8a42-41d2-b440-8ec7f0b19a3b", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "23/11/14 14:47:52 WARN org.apache.spark.sql.catalyst.util.package: Truncated the string representation of a plan since it was too large. This behavior can be adjusted by setting 'spark.sql.debug.maxToStringFields'.\n", - "[Stage 16:=====================================================>(404 + 1) / 405]\r" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "+-------------------------+\n", - "|approx_count_distinct(ID)|\n", - "+-------------------------+\n", - "| 858074|\n", - "+-------------------------+\n", - "\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "from pyspark.sql.functions import approxCountDistinct\n", - "\n", - "df_area.select(approxCountDistinct(\"ID\", rsd = 0.05)).show()" - ] - }, - { - "cell_type": "markdown", - "id": "05c8d38e-9e48-467d-9b52-09c914b2c3f0", - "metadata": {}, - "source": [] - }, - { - "cell_type": "markdown", - "id": "888ce622-bbc0-4ec1-b60f-af8962d6d0b3", - "metadata": {}, - "source": [ - "**Rides per hour**" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "ecbb1412-4e01-4f08-8aca-e523866c9a98", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# rides per hour:\n", - "rides_per_hour = df_area.groupBy(\"hour\").count().orderBy(\"hour\")\n", - "\n", - "# Convert the result to Pandas for local plotting\n", - "rides_per_hour_pd = rides_per_hour.toPandas()\n", - "\n", - "# Plot the data\n", - "plt.figure(figsize=(10, 6))\n", - "plt.bar(rides_per_hour_pd[\"hour\"], rides_per_hour_pd[\"count\"], color=\"skyblue\")\n", - "plt.xlabel(\"Hour of the Day\")\n", - "plt.ylabel(\"Number of Rides\")\n", - "plt.title(\"Number of Rides Per Hour\")\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "aba3e685-0bb7-4afa-9a61-d2f0646886be", - "metadata": {}, - "source": [ - "See a substanial increase in number of rides taking place during program hours. A sizeable jump happens the moment the program starts." - ] - }, - { - "cell_type": "markdown", - "id": "cb9ae09d-c6bc-43d4-824f-a28dc0cb7977", - "metadata": {}, - "source": [ - "**Filter the in-area dataframe to only include rides with a fare under 15, and rides within the timeframe for the given year.**" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "3aa29dbf-f92e-4e0b-9686-15ada9485a8b", - "metadata": {}, - "outputs": [], - "source": [ - "df_area_program = df_area.filter((df_area.fare <= 15.0) & ((df_area.hour >= 17) | (df_area.hour < 4)))" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "c5e8535a-0cd2-4815-bf23-62a7c8bf9210", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "\n", - "df_area_program_pd = df_area_program.toPandas()\n", - "\n", - "plt.figure(figsize=(10, 6))\n", - "sns.histplot(df_area_program_pd['hour'], bins=24, kde=False, color='skyblue')\n", - "plt.title('Distribution of Pickup Hours for Filtered Rides')\n", - "plt.xlabel('Hour of Day')\n", - "plt.ylabel('Number of Rides')\n", - "plt.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "68b385ae-18ab-410c-be47-2cfe371922e1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: folium in /opt/conda/miniconda3/lib/python3.8/site-packages (0.14.0)\n", - "Requirement already satisfied: branca>=0.6.0 in /opt/conda/miniconda3/lib/python3.8/site-packages (from folium) (0.6.0)\n", - "Requirement already satisfied: jinja2>=2.9 in /opt/conda/miniconda3/lib/python3.8/site-packages (from folium) (3.0.3)\n", - "Requirement already satisfied: numpy in /opt/conda/miniconda3/lib/python3.8/site-packages (from folium) (1.19.5)\n", - "Requirement already satisfied: requests in /opt/conda/miniconda3/lib/python3.8/site-packages (from folium) (2.25.1)\n", - "Requirement already satisfied: MarkupSafe>=2.0 in /opt/conda/miniconda3/lib/python3.8/site-packages (from jinja2>=2.9->folium) (2.1.3)\n", - "Requirement already satisfied: chardet<5,>=3.0.2 in /opt/conda/miniconda3/lib/python3.8/site-packages (from requests->folium) (4.0.0)\n", - "Requirement already satisfied: idna<3,>=2.5 in /opt/conda/miniconda3/lib/python3.8/site-packages (from requests->folium) (2.10)\n", - "Requirement already satisfied: urllib3<1.27,>=1.21.1 in /opt/conda/miniconda3/lib/python3.8/site-packages (from requests->folium) (1.25.11)\n", - "Requirement already satisfied: certifi>=2017.4.17 in /opt/conda/miniconda3/lib/python3.8/site-packages (from requests->folium) (2023.7.22)\n", - "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", - "\u001b[0mNote: you may need to restart the kernel to use updated packages.\n" - ] - } - ], - "source": [ - "#pip install folium" - ] - }, - { - "cell_type": "markdown", - "id": "451768f6-f09e-450c-a1e9-8b78d68fd636", - "metadata": {}, - "source": [ - "**heat map of dropoff location and pickup location (for in-program rides)**" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "f9c788a5-0151-4c8d-8036-9207c99dc933", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Collecting plotly\n", - " Downloading plotly-5.18.0-py3-none-any.whl.metadata (7.0 kB)\n", - "Requirement already satisfied: tenacity>=6.2.0 in /opt/conda/miniconda3/lib/python3.8/site-packages (from plotly) (8.2.3)\n", - "Requirement already satisfied: packaging in /opt/conda/miniconda3/lib/python3.8/site-packages (from plotly) (23.2)\n", - "Downloading plotly-5.18.0-py3-none-any.whl (15.6 MB)\n", - "\u001b[2K \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m15.6/15.6 MB\u001b[0m \u001b[31m71.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m:00:01\u001b[0m00:01\u001b[0m\n", - "\u001b[?25hInstalling collected packages: plotly\n", - "Successfully installed plotly-5.18.0\n", - "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\u001b[33m\n", - "\u001b[0m" - ] - } - ], - "source": [ - "import folium\n", - "from folium.plugins import HeatMap\n", - "\n", - "#!pip install plotly\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "73862ba3-eb44-4dbb-b0ad-d162909abb3d", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "import plotly.express as px\n", - "import pandas as pd\n", - "\n", - "# Assuming you have a Pandas DataFrame for in-program rides\n", - "df_area_program_pd = df_area_program.toPandas()\n", - "\n", - "# Create a figure using plotly express\n", - "fig = px.scatter_mapbox(df_area_program_pd, \n", - " lat='pickup_lat', lon='pickup_lon',\n", - " color_discrete_sequence=[\"blue\"], \n", - " zoom=10)\n", - "\n", - "# Add dropoff locations as scatter points on the map\n", - "fig.add_trace(px.scatter_mapbox(df_area_program_pd, \n", - " lat='dropoff_lat', lon='dropoff_lon',\n", - " color_discrete_sequence=[\"red\"]).data[0])\n", - "\n", - "# Update the map layout\n", - "fig.update_layout(mapbox_style=\"carto-positron\", \n", - " mapbox_zoom=10, \n", - " margin={\"r\": 0, \"t\": 0, \"l\": 0, \"b\": 0})\n", - "\n", - "# Show the figure\n", - "fig.show()\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "53de5ddc-a06c-49dd-97e8-0d29d12ce6f4", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import seaborn as sns\n", - "import matplotlib.pyplot as plt\n", - "import pandas as pd\n", - "\n", - "df_area_program_pd = df_area_program.toPandas()\n", - "\n", - "# Create a 2D kernel density estimate plot\n", - "plt.figure(figsize=(12, 8))\n", - "sns.kdeplot(data=df_area_program_pd, x='pickup_lon', y='pickup_lat', cmap='Blues', fill=True, thresh=0, levels=100, alpha=0.8)\n", - "sns.kdeplot(data=df_area_program_pd, x='dropoff_lon', y='dropoff_lat', cmap='Reds', fill=True, thresh=0, levels=100, alpha=0.8)\n", - "\n", - "plt.title('Heatmap of Pickup and Dropoff Locations')\n", - "plt.xlabel('Longitude')\n", - "plt.ylabel('Latitude')\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "e86433b8-89e8-4e72-8c44-d7bcf426673e", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "df_count_plot_program = df_area_program.groupby(\"month\").agg({'ID':'count'}).orderBy(F.col('month').asc()).toPandas() #.plot(x=\"month\",y=\"count(ID)\")\n", - "ax = df_count_plot_program.plot(x=\"month\", y=\"count(ID)\")\n", - "ax.axvline(x=9, color='g', linestyle='--', label='Fall Quarter Begins')\n", - "ax.axvline(x=6, color='r', linestyle='--', label='Spring Quarter Ends')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "c03e5fcb-f4dc-4209-8adc-d5cb33113e88", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# basic plots for all rides (not just in the program area)\n", - "df_2022.groupby(\"month\").agg({'ID':'count'}).orderBy(F.col('month').asc()).toPandas().plot(x=\"month\")" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "ded2ecf1-3bff-418a-975c-4cf286c0985e", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "df_total = df_2022.groupby(\"pickup_area\").agg({'ID':'count'}).orderBy(F.col('pickup_area').asc()).toPandas()" - ] - }, - { - "cell_type": "code", - "execution_count": 23, - "id": "4c020195-2502-4f62-a81e-1d10344a800b", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "%matplotlib inline\n", - "plt.figure(figsize=(10, 10))\n", - "ax = df_total.plot(x=\"pickup_area\",y=\"count(ID)\", kind='bar')\n", - "plt.xticks(rotation=45, ha='right')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 24, - "id": "4c1408b3-df0d-4078-b266-b398fa80983a", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 24, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "df_2022.groupby(\"dropoff_area\").agg({'ID':'count'}).orderBy(F.col('dropoff_area').asc()).toPandas().plot(x=\"dropoff_area\",y=\"count(ID)\", kind='bar')" - ] - }, - { - "cell_type": "code", - "execution_count": 33, - "id": "02bde50b-4bdf-45fe-b101-a6047b7597ef", - "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - " \r" - ] - } - ], - "source": [ - "# storing data on the bucket\n", - "df_area_program.write.option(\"header\", \"true\").csv(\"gs://msca-bdp-student-gcs/bdp-rideshare-project/rideshare/processed_data/program_area_time_rides_2022.csv\")" - ] - }, - { - "cell_type": "markdown", - "id": "b54d43b4-5ef0-466c-a8b4-1cc3e4d8690f", - "metadata": {}, - "source": [ - "### Next Steps\n", - "\n", - "the geospatial ipynb (notebook 4.8) from ashish shows some ways to work with this kind of data in pyspark\n", - "\n", - "Plot Cloropleths (for all of chicago)\n", - "\n", - "heat map of dropoff location and pickup location (for in-program rides)\n", - "\n", - "add vertical lines at and key shifts in the program policy" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "1534c257-6dba-4183-ac01-a4d2820a182e", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "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": "3.8.15" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -}