From 3c79176cc1581e54880745aff66bafe7abbd260b Mon Sep 17 00:00:00 2001 From: root Date: Thu, 16 Nov 2023 01:36:30 +0000 Subject: [PATCH] finalized graphs and put clean data in bucket --- eda_2021.ipynb | 135 ++++++++++++++++++++++++++++++++----------------- 1 file changed, 88 insertions(+), 47 deletions(-) diff --git a/eda_2021.ipynb b/eda_2021.ipynb index 5466719..402be1d 100644 --- a/eda_2021.ipynb +++ b/eda_2021.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "201288da-86ac-4db0-a56b-4d75e26e1753", "metadata": {}, "outputs": [], @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "3443992c-4530-48f2-a133-fb1dacf4b84f", "metadata": {}, "outputs": [ @@ -28,10 +28,7 @@ " ('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.history.fs.logDirectory',\n", - " 'gs://dataproc-temp-us-central1-635155370842-uzamlpgc/ef995586-ab93-4aae-8a58-b7f73789ab77/spark-job-history'),\n", " ('spark.dataproc.sql.joinConditionReorder.enabled', 'true'),\n", - " ('spark.ui.proxyBase', '/proxy/application_1700083397876_0002'),\n", " ('spark.kryoserializer.buffer.max', '2000M'),\n", " ('spark.serializer', 'org.apache.spark.serializer.KryoSerializer'),\n", " ('spark.dataproc.sql.local.rank.pushdown.enabled', 'true'),\n", @@ -43,13 +40,10 @@ " ('spark.metrics.namespace',\n", " 'app_name:${spark.app.name}.app_id:${spark.app.id}'),\n", " ('spark.executor.memory', '4g'),\n", - " ('spark.eventLog.dir',\n", - " 'gs://dataproc-temp-us-central1-635155370842-uzamlpgc/ef995586-ab93-4aae-8a58-b7f73789ab77/spark-job-history'),\n", " ('spark.dataproc.sql.optimizer.leftsemijoin.conversion.enabled', 'true'),\n", - " ('spark.org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter.param.PROXY_URI_BASES',\n", - " 'http://hub-msca-bdp-dphub-students-abejburton-m:8088/proxy/application_1700083397876_0002'),\n", " ('spark.hadoop.hive.execution.engine', 'mr'),\n", " ('spark.executor.id', 'driver'),\n", + " ('spark.app.startTime', '1700095565609'),\n", " ('spark.hadoop.mapreduce.fileoutputcommitter.algorithm.version', '2'),\n", " ('spark.dynamicAllocation.maxExecutors', '10000'),\n", " ('spark.org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter.param.PROXY_HOSTS',\n", @@ -66,7 +60,8 @@ " 'com.johnsnowlabs.nlp_spark-nlp_2.12-4.4.0.jar,graphframes_graphframes-0.8.2-spark3.1-s_2.12.jar,com.typesafe_config-1.4.2.jar,org.rocksdb_rocksdbjni-6.29.5.jar,com.amazonaws_aws-java-sdk-bundle-1.11.828.jar,com.github.universal-automata_liblevenshtein-3.0.0.jar,com.google.cloud_google-cloud-storage-2.16.0.jar,com.navigamez_greex-1.0.jar,com.johnsnowlabs.nlp_tensorflow-cpu_2.12-0.4.4.jar,it.unimi.dsi_fastutil-7.0.12.jar,org.projectlombok_lombok-1.16.8.jar,com.google.guava_guava-31.1-jre.jar,com.google.guava_failureaccess-1.0.1.jar,com.google.guava_listenablefuture-9999.0-empty-to-avoid-conflict-with-guava.jar,com.google.errorprone_error_prone_annotations-2.16.jar,com.google.j2objc_j2objc-annotations-1.3.jar,com.google.http-client_google-http-client-1.42.3.jar,io.opencensus_opencensus-contrib-http-util-0.31.1.jar,com.google.http-client_google-http-client-jackson2-1.42.3.jar,com.google.http-client_google-http-client-gson-1.42.3.jar,com.google.api-client_google-api-client-2.1.1.jar,commons-codec_commons-codec-1.15.jar,com.google.oauth-client_google-oauth-client-1.34.1.jar,com.google.http-client_google-http-client-apache-v2-1.42.3.jar,com.google.apis_google-api-services-storage-v1-rev20220705-2.0.0.jar,com.google.code.gson_gson-2.10.jar,com.google.cloud_google-cloud-core-2.9.0.jar,com.google.auto.value_auto-value-annotations-1.10.1.jar,com.google.cloud_google-cloud-core-http-2.9.0.jar,com.google.http-client_google-http-client-appengine-1.42.3.jar,com.google.api_gax-httpjson-0.105.1.jar,com.google.cloud_google-cloud-core-grpc-2.9.0.jar,io.grpc_grpc-core-1.51.0.jar,com.google.api_gax-2.20.1.jar,com.google.api_gax-grpc-2.20.1.jar,io.grpc_grpc-alts-1.51.0.jar,io.grpc_grpc-grpclb-1.51.0.jar,org.conscrypt_conscrypt-openjdk-uber-2.5.2.jar,io.grpc_grpc-protobuf-1.51.0.jar,com.google.auth_google-auth-library-credentials-1.13.0.jar,com.google.auth_google-auth-library-oauth2-http-1.13.0.jar,com.google.api_api-common-2.2.2.jar,javax.annotation_javax.annotation-api-1.3.2.jar,io.opencensus_opencensus-api-0.31.1.jar,io.grpc_grpc-context-1.51.0.jar,com.google.api.grpc_proto-google-iam-v1-1.6.22.jar,com.google.protobuf_protobuf-java-3.21.10.jar,com.google.protobuf_protobuf-java-util-3.21.10.jar,com.google.api.grpc_proto-google-common-protos-2.11.0.jar,org.threeten_threetenbp-1.6.4.jar,com.google.api.grpc_proto-google-cloud-storage-v2-2.16.0-alpha.jar,com.google.api.grpc_grpc-google-cloud-storage-v2-2.16.0-alpha.jar,com.google.api.grpc_gapic-google-cloud-storage-v2-2.16.0-alpha.jar,com.fasterxml.jackson.core_jackson-core-2.14.1.jar,com.google.code.findbugs_jsr305-3.0.2.jar,io.grpc_grpc-api-1.51.0.jar,io.grpc_grpc-auth-1.51.0.jar,io.grpc_grpc-stub-1.51.0.jar,org.checkerframework_checker-qual-3.28.0.jar,com.google.api.grpc_grpc-google-iam-v1-1.6.22.jar,io.grpc_grpc-protobuf-lite-1.51.0.jar,com.google.android_annotations-4.1.1.4.jar,org.codehaus.mojo_animal-sniffer-annotations-1.22.jar,io.grpc_grpc-netty-shaded-1.51.0.jar,io.perfmark_perfmark-api-0.26.0.jar,io.grpc_grpc-googleapis-1.51.0.jar,io.grpc_grpc-xds-1.51.0.jar,io.opencensus_opencensus-proto-0.2.0.jar,io.grpc_grpc-services-1.51.0.jar,com.google.re2j_re2j-1.6.jar,dk.brics.automaton_automaton-1.11-8.jar,org.slf4j_slf4j-api-1.7.16.jar'),\n", " ('spark.repl.local.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.app.id', 'application_1700083397876_0002'),\n", + " ('spark.org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter.param.PROXY_URI_BASES',\n", + " 'http://hub-msca-bdp-dphub-students-abejburton-m:8088/proxy/application_1700094704615_0002'),\n", " ('spark.driver.host',\n", " 'hub-msca-bdp-dphub-students-abejburton-m.c.msca-bdp-student-ap.internal'),\n", " ('spark.sql.cbo.enabled', 'true'),\n", @@ -83,34 +78,39 @@ " ('spark.yarn.am.memory', '640m'),\n", " ('spark.cores.max', '4'),\n", " ('spark.executor.cores', '4'),\n", + " ('spark.app.id', 'application_1700094704615_0002'),\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.history.fs.logDirectory',\n", + " 'gs://dataproc-temp-us-central1-635155370842-uzamlpgc/2bfcb1ba-12f1-4fdd-8722-7dc6c9d23e48/spark-job-history'),\n", " ('spark.executor.instances', '2'),\n", " ('spark.dataproc.listeners',\n", " 'com.google.cloud.spark.performance.DataprocMetricsListener'),\n", - " ('spark.driver.appUIAddress',\n", - " 'http://hub-msca-bdp-dphub-students-abejburton-m.c.msca-bdp-student-ap.internal:42687'),\n", " ('spark.serializer.objectStreamReset', '100'),\n", " ('spark.submit.deployMode', 'client'),\n", + " ('spark.driver.port', '35653'),\n", " ('spark.sql.cbo.joinReorder.enabled', 'true'),\n", + " ('spark.eventLog.dir',\n", + " 'gs://dataproc-temp-us-central1-635155370842-uzamlpgc/2bfcb1ba-12f1-4fdd-8722-7dc6c9d23e48/spark-job-history'),\n", " ('spark.shuffle.service.enabled', 'true'),\n", - " ('spark.driver.port', '35485'),\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.app.startTime', '1700085601972'),\n", + " ('spark.ui.proxyBase', '/proxy/application_1700094704615_0002'),\n", " ('spark.master', 'yarn'),\n", " ('spark.ui.port', '0'),\n", " ('spark.rpc.message.maxSize', '512'),\n", " ('spark.rdd.compress', 'True'),\n", + " ('spark.driver.appUIAddress',\n", + " 'http://hub-msca-bdp-dphub-students-abejburton-m.c.msca-bdp-student-ap.internal:39485'),\n", " ('spark.task.maxFailures', '10'),\n", " ('spark.yarn.isPython', 'true'),\n", " ('spark.dynamicAllocation.enabled', 'true'),\n", " ('spark.ui.showConsoleProgress', 'true')]" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -127,7 +127,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, "id": "a10a9fef-7517-4947-a7a5-b17db05dbb79", "metadata": {}, "outputs": [ @@ -580,27 +580,24 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 6, "id": "46e2e9e5-3581-444c-b149-827a5cbc62f5", "metadata": {}, "outputs": [], "source": [ "# Working with just data that contains full information and check for dupes\n", "df_2021 = df_2021.dropna(how='any', subset=['Trip Start Timestamp','Trip End Timestamp','Fare','Dropoff Community Area','Pickup Community Area'])\n", - "df_2021 = df_2021.dropDuplicates()\n", - "# df_2021.count()" + "df_2021 = df_2021.dropDuplicates()" ] }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 7, "id": "6a52d857-bc07-47a7-8cc9-71478bf10e08", "metadata": {}, "outputs": [], "source": [ "# Drop columns unlikely to be useful for analysis for speed of computation and rename columns to remove spacing for ease of code writing\n", - "#spark.conf.set(\"spark.sql.legacy.timeParserPolicy\", \"LEGACY\")\n", - "\n", "df_2021 = df_2021.drop('Trips Pooled','Additional Charges','Shared Trip Authorized','Pickup Centroid Location','Dropoff Centroid Location')\n", "df_2021 = df_2021.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", @@ -614,21 +611,52 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 8, "id": "17ebe569-82bb-49b0-aaaf-ac5062bede35", "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "[Stage 6:> (0 + 1) / 1]\r" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "+--------------------+-------------------+-------------------+-------+-----+------------+-------------+-----------+------------+----+---+-----+-------------+--------------+-------------+--------------+-----+------------+----+---+\n", + "| ID| start_timestamp| end_timestamp|seconds|miles|pickup_tract|dropoff_tract|pickup_area|dropoff_area|Fare|Tip|total| pickup_lat| pickup_lon| dropoff_lat| dropoff_lon|month|day_of_month|hour|day|\n", + "+--------------------+-------------------+-------------------+-------+-----+------------+-------------+-----------+------------+----+---+-----+-------------+--------------+-------------+--------------+-----+------------+----+---+\n", + "|76d913bb3f0771ab2...|2021-01-01 00:00:00|2021-01-01 00:15:00| 1039| 5.9| null| null| 44| 39|20.0| 0|21.23|41.7402057565|-87.6159695226|41.8089162826|-87.5961833442| 1| 1| 0| 6|\n", + "|6ebae7e105b93a085...|2021-01-01 00:15:00|2021-01-01 00:15:00| 285| 2.4| 17031833100| 17031839100| 28| 32| 5.0| 0| 12.1|41.8790669938| -87.657005027|41.8809944707|-87.6327464887| 1| 1| 0| 6|\n", + "|ba7d98f8744740a4b...|2021-01-01 00:15:00|2021-01-01 00:30:00| 277| 1.1| 17031842300| 17031842200| 24| 8| 2.5| 0| 5.6|41.8983058696|-87.6536139825|41.9049353016|-87.6499072264| 1| 1| 0| 6|\n", + "+--------------------+-------------------+-------------------+-------+-----+------------+-------------+-----------+------------+----+---+-----+-------------+--------------+-------------+--------------+-----+------------+----+---+\n", + "only showing top 3 rows\n", + "\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + " \r" + ] + } + ], "source": [ "# add the month column\n", "df_2021 = df_2021.withColumn('month', F.month(df_2021.start_timestamp))\n", "df_2021 = df_2021.withColumn('day_of_month', F.dayofmonth(df_2021.start_timestamp))\n", "df_2021 = df_2021.withColumn('hour', F.hour(df_2021.start_timestamp))\n", - "df_2021 = df_2021.withColumn('day', F.dayofweek(df_2021.start_timestamp))" + "df_2021 = df_2021.withColumn('day', F.dayofweek(df_2021.start_timestamp))\n", + "df_2021.show(3)" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 16, "id": "38ae8fc8-7d8b-4560-a6fb-7d84fc672929", "metadata": {}, "outputs": [ @@ -646,7 +674,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 17, "id": "fdd98395-7ec5-413f-975c-db44d2871c46", "metadata": {}, "outputs": [ @@ -660,22 +688,25 @@ "Tip int32\n", "total float64\n", "miles float64\n", - "seconds int32\n", + "seconds float64\n", + "hour int32\n", + "day int32\n", + "month int32\n", "dtype: object" ] }, - "execution_count": 16, + "execution_count": 17, "metadata": {}, "output_type": "execute_result" } ], "source": [ - "sample_df.head()" + "sample_df.dtypes" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 19, "id": "064352aa-8513-4953-b527-48cc322fdfab", "metadata": {}, "outputs": [], @@ -686,7 +717,7 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 20, "id": "a81f2984-28da-4dbb-9645-7615f81c1b67", "metadata": {}, "outputs": [], @@ -703,8 +734,9 @@ "outputs": [], "source": [ "import seaborn as sns\n", + "import matplotlib.pyplot as plt\n", "sns.set_theme(style=\"ticks\")\n", - "sns.pairplot(sample_df)\n", + "sns.pairplot(sample_df, hue='dropoff_area')\n", "plt.show()" ] }, @@ -834,7 +866,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 23, "id": "2ae6d6b2-9001-4ded-ba3a-225861cbe451", "metadata": {}, "outputs": [], @@ -971,7 +1003,7 @@ "outputs": [], "source": [ "# verify this is the correct time period for your given year\n", - "df_area_program_1 = df_area.filter((df_area.Fare <= 15.0) & ((df_area.hour >= 21) | (df_area.hour < 4)) & (df_area.day >= 3) & ((df_area.month == 10) | ((df_area.month == 11) & (df_area.day_of_month < 11))))\n", + "df_area_program_1 = df_area.filter((df_area.Fare <= 15.0) & ((df_area.hour >= 21) | (df_area.hour < 4)) & ((df_area.day >= 3) & (df_area.day < 6)) & ((df_area.month == 10) | ((df_area.month == 11) & (df_area.day_of_month < 11))))\n", "df_area_program_2 = df_area.filter((df_area.Fare <= 15.0) & ((df_area.hour >= 17) | (df_area.hour < 4)) & ((df_area.month == 12) | ((df_area.month == 11) & (df_area.day_of_month > 11))))\n", "df_area_program = df_area_program_1.union(df_area_program_2)" ] @@ -994,7 +1026,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "[Stage 117:==================================================> (36 + 3) / 39]\r" + "[Stage 25:=================================> (40 + 10) / 66]\r" ] }, { @@ -1004,7 +1036,7 @@ "+-------------------------+\n", "|approx_count_distinct(ID)|\n", "+-------------------------+\n", - "| 123125|\n", + "| 36889|\n", "+-------------------------+\n", "\n" ] @@ -1013,19 +1045,20 @@ "name": "stderr", "output_type": "stream", "text": [ - " \r" + "23/11/16 01:18:12 WARN org.apache.spark.scheduler.cluster.YarnSchedulerBackend$YarnSchedulerEndpoint: Requesting driver to remove executor 1 for reason Container marked as failed: container_1700094704615_0002_01_000001 on host: hub-msca-bdp-dphub-students-abejburton-sw-w0bj.c.msca-bdp-student-ap.internal. Exit status: -100. Diagnostics: Container released on a *lost* node.\n", + "23/11/16 01:18:12 ERROR org.apache.spark.scheduler.cluster.YarnScheduler: Lost executor 1 on hub-msca-bdp-dphub-students-abejburton-sw-w0bj.c.msca-bdp-student-ap.internal: Container marked as failed: container_1700094704615_0002_01_000001 on host: hub-msca-bdp-dphub-students-abejburton-sw-w0bj.c.msca-bdp-student-ap.internal. Exit status: -100. Diagnostics: Container released on a *lost* node.\n" ] } ], "source": [ "from pyspark.sql.functions import approxCountDistinct\n", "\n", - "df_area_program.select(approxCountDistinct(\"ID\", rsd = 0.05)).show()" + "df_area_program.select(approxCountDistinct(\"ID\", rsd = 0.20)).show()" ] }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 27, "id": "4170f6ac-afca-44c9-9e2e-7e78670de3d1", "metadata": {}, "outputs": [ @@ -1038,7 +1071,7 @@ }, { "data": { - "image/png": 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", + "image/png": 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", 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" ] @@ -1050,15 +1083,15 @@ "source": [ "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='Program Starts, Fall Quarter Begins')\n", - "ax.axvline(x=6, color='r', linestyle='--', label='Spring Quarter Ends')\n", + "ax.axvline(x=10, color='g', linestyle='--', label='Program Starts, 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": 26, + "execution_count": 28, "id": "d266e90c-ae57-41cb-99a5-3185b61e60ed", "metadata": {}, "outputs": [ @@ -1071,7 +1104,7 @@ }, { "data": { - "image/png": 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", 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" ] @@ -1225,10 +1258,18 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 29, "id": "4876aef0-e741-4302-82d5-24f133f1d762", "metadata": {}, - "outputs": [], + "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_2021.csv\")\n",