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Fixes markdown formatting #149

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Jun 21, 2022
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Fixes markdown formatting #149

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50 changes: 19 additions & 31 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -6,7 +6,7 @@ The Optimus Prime Database Assessment tool is used to assess homogenous migratio
2. A python script (.py) to import data into Google Big Query
3. A Data Studio template that can be used to generate assessment report

NOTE: The script to collect data only runs SELECT statements against Oracle dictionary and requires read permissions. No application data is accessed, nor is any data changed or deleted.
> NOTE: The script to collect data only runs SELECT statements against Oracle dictionary and requires read permissions. No application data is accessed, nor is any data changed or deleted.

# How to use this tool

Expand All @@ -15,7 +15,7 @@ NOTE: The script to collect data only runs SELECT statements against Oracle dict
1.1. Database user creation.

Create an Oracle database user -or- choose an existing user account .
* If you decide to use an existing database user with all the privileges already assigned please go to Step 1.3.
* If you decide to use an existing database user with all the privileges already assigned please go to Step 1.3.


```
Expand All @@ -26,15 +26,13 @@ create user C##optimusprime identified by "mysecretPa33w0rd";

if creating a application user within a PDB create a regular user
create user optimusprime identified by "mysecretPa33w0rd";

```

1.2. Clone *optimus prime* into your work directory in a client machine that has connectivity to your databases

```
cd <work-directory>
git clone https://github.com/GoogleCloudPlatform/oracle-database-assessment

```

1.3. Verfiy 3 Grants scripts under (@/<work-directory>/oracle-database-assessment/db_assessment/dbSQLCollector/)
Expand All @@ -48,11 +46,10 @@ git clone https://github.com/GoogleCloudPlatform/oracle-database-assessment
```
@/<work-directory>/oracle-database-assessment/db_assessment/dbSQLCollector/grants_wrapper.sql
Please enter the DB Local Username(Or CDB Username) to receive all required grants: [C##]optimusprime

```


NOTE: grants_wrapper.sql has provided variable db_awr_license which is set default to Y to access AWR tables. AWR is a licensed feature of Oracle. If you don't have license to run AWR you can disable flag and it will execute script minimum_select_grants_for_targets_ONLY_FOR_11g.sql.
> NOTE: grants_wrapper.sql has provided variable db_awr_license which is set default to Y to access AWR tables. AWR is a licensed feature of Oracle. If you don't have license to run AWR you can disable flag and it will execute script minimum_select_grants_for_targets_ONLY_FOR_11g.sql.

OR

Expand All @@ -63,34 +60,30 @@ For Database version 11g and below
```
@/<work-directory>/oracle-database-assessment/db_assessment/dbSQLCollector/minimum_select_grants_for_targets_ONLY_FOR_11g.sql
Please enter the DB Local Username(Or CDB Username) to receive all required grants: [C##]optimusprime

```

For Database version 12c and above

```
@/<work-directory>/oracle-database-assessment/db_assessment/dbSQLCollector/minimum_select_grants_for_targets_12c_AND_ABOVE.sql

```

1.4. Execute /home/oracle/oracle-database-assessment/db_assessment/dbSQLCollector/collectData-Step1.sh to start collecting the data.
* Execute this from a system that can access your database via sqlplus
* Pass connect string as input to this script (see below for example)
* NOTE: If this is an Oracle RAC and/or PDB environment you just need to run it once per database. No need to run in each PDB or in each Oracle RAC instance.
* Execute this from a system that can access your database via sqlplus
* Pass connect string as input to this script (see below for example)
* NOTE: If this is an Oracle RAC and/or PDB environment you just need to run it once per database. No need to run in each PDB or in each Oracle RAC instance.

```

mkdir -p /<work-directory>/oracle-database-assessment-output

cd /<work-directory>/oracle-database-assessment-output

/<work-directory>/oracle-database-assessment/db_assessment/dbSQLCollector/collectData-Step1.sh optimusprime/mysecretPa33w0rd@//<serverhost>/<servicename>

```

1.5. Once the script is executed you should see many opdb\*.log output files generated. It is recommended to zip/tar these files.
* All the generated files follow this standard `opdb__<queryname>__<dbversion>_<scriptversion>_<hostname>_<dbname>_<instancename>_<datetime>.log`
* Use meaningful names when zip/tar the files.
* All the generated files follow this standard `opdb__<queryname>__<dbversion>_<scriptversion>_<hostname>_<dbname>_<instancename>_<datetime>.log`
* Use meaningful names when zip/tar the files.

```
Example output:
Expand Down Expand Up @@ -125,19 +118,16 @@ opdb__dbservicesinfo__122_0.1.1_oracle12c.ORCL.orcl.080421224807.log
gcloud auth list

gcloud config set project <project id>

```

2.2 Export Environment variables. (Step 1.2 has working directory created)

```

export OP_WORKDING_DIR=<<path for working directory>
export OP_BQ_DATASET=<<BigQuery Dataset Name>>
export OP_OUTPUT_DIR=/$OP_WORKDING_DIR/oracle-database-assessment-output/<<assessment output directory>
mkdir $OP_OUTPUT_DIR/log
export OP_LOG_DIR=$OP_OUTPUT_DIR/log

```

2.3 Create working directory (Skip if you have followed step 1.2 on same server)
Expand Down Expand Up @@ -168,8 +158,8 @@ unzip <<zip files>>
```

2.7. [Create a service account and download the key](https://cloud.google.com/iam/docs/creating-managing-service-accounts#before-you-begin ) .
* Set GOOGLE_APPLICATION_CREDENTIALS to point to the downloaded key. Make sure the service account has BigQuery Admin privelege.
* NOTE: This step can be skipped if using [Cloud Shell](https://ssh.cloud.google.com/cloudshell/)
* Set GOOGLE_APPLICATION_CREDENTIALS to point to the downloaded key. Make sure the service account has BigQuery Admin privelege.
* NOTE: This step can be skipped if using [Cloud Shell](https://ssh.cloud.google.com/cloudshell/)

2.8. Create a python virtual environment to install dependencies and execute the `optimusprime.py` script

Expand Down Expand Up @@ -198,8 +188,6 @@ unzip <<zip files>>
If you want to akip all file validations

python optimusprime.py -dataset newdatasetORexistingdataset -collectionid "" -fileslocation /<work-directory>/oracle-database-assessment-output -projectname my-awesome-gcp-project -skipvalidations


```

* `-dataset`: is the name of the dataset in Google Big Query. It is created if it does not exists. If it does already nothing to do then.
Expand All @@ -214,7 +202,7 @@ unzip <<zip files>>
* `-filterbydbversion`: This an optional. In case you have files from multiple db versions in the folder and you want to load only specific db version files
* `-skipvalidations`: This is optional. Default is False. if we use the flag, file validations will be skipped

* NOTE: If your file has elapsed time or any other string except data, fun following script to remove it
* >NOTE: If your file has elapsed time or any other string except data, fun following script to remove it

```
for i in `grep "Elapsed:" $OP_OUTPUT_DIR/*.log | cut -d ":" -f 1`; do sed -i '$ d' $i; done
Expand All @@ -223,14 +211,14 @@ for i in `grep "Elapsed:" $OP_OUTPUT_DIR/*.log | cut -d ":" -f 1`; do sed -i '$
## Step 3 - Analyzing imported data

3.1. Open the dataset used in the step 2 of Part 2 in Google Big Query
* Query the viewnames starting with vReport* for further analysis
* Sample queries are listed, they provide
* Source DB Summary
* Source Host details
* Google Bare Metal Sizing
* Google Bare Metal Pricing
* Migration Recommendations
* Sample [Assessment Report](report/Optimus_Prime_-_dashboard.pdf), was created in DataStudio. A similar report can be generated using the queries for your datasets as part of the assessment readout.
* Query the viewnames starting with vReport* for further analysis
* Sample queries are listed, they provide
* Source DB Summary
* Source Host details
* Google Bare Metal Sizing
* Google Bare Metal Pricing
* Migration Recommendations
* Sample [Assessment Report](report/Optimus_Prime_-_dashboard.pdf), was created in DataStudio. A similar report can be generated using the queries for your datasets as part of the assessment readout.

## Contributing to the project

Expand Down