feat: add cool shell script

COOL-cohort · Aug 13, 2024 · edfe393 · edfe393
1 parent da9a1d8
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diff --git a/README.md b/README.md
@@ -37,7 +37,7 @@ mvn clean package
 
 ### Required sources
 
-1. **dataset file**: a CSV file with "," delimiter (normally dumped from a database table), and the table header removed.
+1. **dataset file**: a CSV file with "," delimiter (normally dumped from a database table) and the table header removed.
 2. **dataset schema file**: a `table.yaml` file specifying the dataset's columns and their measure fields.
 3. **query file**: a YAML file specifying the parameters for the running query server.
 
@@ -46,8 +46,7 @@ mvn clean package
 Before query processing, we need to load the dataset into COOL native format. The sample code to load csv dataset with data loader can be found in [CsvLoader.java](cool-core/src/main/java/com/nus/cool/functionality/CsvLoader.java).
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CsvLoader \
+./cool load \
     dataset \
     path/to/your/.yaml \
     path/to/your/datafile \
@@ -56,7 +55,7 @@ java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
 
 The five arguments in the command have the following meaning:
 
-1. a unique dataset name given under the directory
+1. the dataset name
 2. the `table.yaml` (the third required source)
 3. the dataset file (the first required source)
 4. the output directory for the compacted dataset
@@ -70,35 +69,31 @@ We provide an example for cohort query processing in [CohortAnalysis.java](cool-
 #### Cohort Selection
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CohortSelection \
+./cool cohortselection \
     path/to/output/datasource/directory \
     path/to/your/queryfile
 ```
 
 #### Cohort Query
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CohortAnalysis \
+./cool cohortquery \
     path/to/output/datasource/directory \
     path/to/your/cohortqueryfile
 ```
 
 #### Funnel Query
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.FunnelAnalysis \
+./cool funnelquery \
     path/to/output/datasource/directory \
     path/to/your/funnelqueryfile
 ```
 
 #### OLAP Query
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.IcebergLoader \
+./cool olapquery \
     path/to/output/datasource/directory \
     path/to/your/queryfile
 ```
@@ -112,8 +107,7 @@ We have provided examples in `sogamo` directory and `health_raw` directory. Now
 The COOL system supports CSV data format by default, and you can load `sogamo` dataset with the following command.
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CsvLoader \
+./cool load \
     sogamo \
     datasets/sogamo/table.yaml \
     datasets/sogamo/data.csv \
@@ -161,8 +155,7 @@ There will be a cube generated under the `./CubeRepo` directory, which is named
 Similarly, load the `health_raw` dataset with:
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CsvLoader \
+./cool load \
     health_raw \
     datasets/health_raw/table.yaml \
     datasets/health_raw/data.csv \
@@ -176,24 +169,23 @@ We use the `health_raw` dataset for example to demonstrate the cohort analysis.
 #### Select the specific users
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CohortSelection \
+./cool cohortselection \
     ./CubeRepo \
     datasets/health_raw/sample_query_selection/query.json
 ```
 
 where the arguments are:
 
 1. `./CubeRepo`: the output directory for the compacted dataset
-2. `datasets/health_raw/sample_query_selection/query.json`: the JSON file for the cohort query
+2. `datasets/health_raw/sample_query_selection/query.json`: the cohort query (in JSON)
 
 <!--
 - Display all selected records of the cohort in the terminal for exploration
 
 ```bash
 java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
     com.nus.cool.functionality.CohortExploration \
-    CubeRepo \
+    ./CubeRepo \
     health_raw \
     sample_query_selection
 ```
@@ -202,8 +194,7 @@ java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
 #### Execute cohort query
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CohortAnalysis \
+./cool cohortquery \
     ./CubeRepo \
     datasets/health_raw/sample_query_average/query.json
 ```
@@ -213,8 +204,7 @@ java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
 We use the `sogamo` dataset for example to demonstrate the funnel analysis.
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.FunnelAnalysis \
+./cool funnelquery \
     ./CubeRepo \
     datasets/sogamo/sample_funnel_analysis/query.json
 ```
@@ -228,8 +218,7 @@ We have provided examples in `olap-tpch` directory.
 The COOL system supports CSV data format by default, and you can load `tpc-h` dataset with the following command.
 
 ```bash
-java -cp ./cool-core/target/cool-core-0.1-SNAPSHOT.jar \
-    com.nus.cool.functionality.CsvLoader \
+./cool load \
     tpc-h-10g \
     datasets/olap-tpch/table.yaml \
     datasets/olap-tpch/scripts/data.csv \
@@ -244,10 +233,10 @@ Run Server
 
 1. put the `application.property` file at the same level as the .jar file.
 2. edit the server configuration in the `application.property` file.
-3. run the below command line.
+3. run the below command.
 
 ```bash
-java -jar cool-queryserver/target/cool-queryserver-0.1-SNAPSHOT.jar
+./cool server
 ```
 
 ## CONNECT TO EXTERNAL STORAGE SERVICES

diff --git a/cool b/cool
@@ -0,0 +1,65 @@
+#!/usr/bin/env bash
+
+COOL_CORE_PATH="${COOL_CORE_JAR_PATH:-./cool-core/target/cool-core-0.1-SNAPSHOT.jar}"
+COOL_QUERY_SERVER_PATH="${COOL_QUERY_SERVER_PATH:-./cool-queryserver/target/cool-queryserver-0.1-SNAPSHOT.jar}"
+
+
+main_help() {
+    COOL_HELP_LEFT_ALIGN="%-17s"
+
+    echo "Usage: $0 <command> [<args>]"
+    echo
+    echo Commands
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "help" "Show this help menu"
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "load" "Load dataset"
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "cohortselection" "Perform cohort selection"
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "cohortquery" "Perform cohort query"
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "funnelquery" "Perform funnel query"
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "olapquery" "Perform OLAP query"
+    printf "   $COOL_HELP_LEFT_ALIGN %s\n" "server" "Start query server"
+
+    exit ${1:-0}
+}
+
+main_load() {
+    java -cp $COOL_CORE_PATH com.nus.cool.functionality.CsvLoader "$@"
+}
+
+main_cohortselection() {
+    java -cp $COOL_CORE_PATH com.nus.cool.functionality.CohortSelection "$@"
+}
+
+main_cohortquery() {
+    java -cp $COOL_CORE_PATH com.nus.cool.functionality.CohortAnalysis "$@"
+}
+
+main_funnelquery() {
+    java -cp $COOL_CORE_PATH com.nus.cool.functionality.FunnelAnalysis "$@"
+}
+
+main_olapquery() {
+    java -cp $COOL_CORE_PATH com.nus.cool.functionality.IcebergLoader "$@"
+}
+
+main_server() {
+    java -jar $COOL_QUERY_SERVER_PATH
+}
+
+function main() {
+    if (($# == 0)); then
+        main_help 0
+    fi
+
+    case ${1} in
+    help | load | cohortselection | cohortquery | funnelquery | olapquery | server)
+        "main_$1" "${@:2}"
+        ;;
+    *)
+        echo "unknown command: $1"
+        main_help 1
+        exit 1
+        ;;
+    esac
+}
+
+main "$@"