[GitHub] [carbondata] maheshrajus opened a new pull request #4140: [CARBONDATA-4192] UT cases correction for validating the exception message correctly

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maheshrajus opened a new pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140


   
    ### Why is this PR needed?
    Currently, when we check the exception message like below, it is not asserting/failing/catching if the message content is different.
   ```
   intercept[UnsupportedOperationException](
   sql("update test set(a)=(4) where id=1").collect()).getMessage.contains("abc")
   ```
   
    ### What changes were proposed in this PR?
   1) Added assert condition like below for validating the exception message correctly
   ```
   assert(intercept[UnsupportedOperationException](
   sql("update test set(a)=(4) where id=1").collect()).getMessage.contains("abc"))
   ```
   2) Added assert condition to check exception message for some test cases which are not checking exception message
   3) Fixed add segment doc heading related issues
    ### Does this PR introduce any user interface change?
    - No
    ### Is any new testcase added?
    - No
   
   


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-847857763


   Build Success with Spark 2.4.5, Please check CI http://121.244.95.60:12602/job/ApacheCarbon_PR_Builder_2.4.5/3681/
   


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-847859992


   Build Success with Spark 2.3.4, Please check CI http://121.244.95.60:12602/job/ApacheCarbonPRBuilder2.3/5426/
   


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Indhumathi27 commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644496057



##########
File path: docs/addsegment-guide.md
##########
@@ -51,7 +51,7 @@ To support multiple formats per segment basis we can create multiple RDD using t
 Note: This integration will be clean as we use the sparks optimized reading, pruning and it

Review comment:
       ```suggestion
   **Note**: This integration will be clean as we use the sparks optimized reading, pruning and it
   ```

##########
File path: docs/addsegment-guide.md
##########
@@ -37,12 +37,12 @@ In the above command user can add the existing data to the carbon table as a new
 During add segment, it will infer the schema from data and validates the schema against the carbon table.
 If the schema doesn’t match it throws an exception.
 
-###Changes to tablestatus file
+### Changes to tablestatus file

Review comment:
       Please change line 441 ‘format’  to `format`

##########
File path: docs/addsegment-guide.md
##########
@@ -17,14 +17,14 @@
 
 # Heterogeneous format segments in carbondata
 
-###Background
+### Background
 In the industry, many users already adopted to data with different formats like ORC, Parquet, JSON, CSV etc.,  
 If users want to migrate to Carbondata for better performance or for better features then there is no direct way.
 All the existing data needs to be converted to Carbondata to migrate.  
 This solution works out if the existing data is less, what if the existing data is more?  
 Heterogeneous format segments aims to solve this problem by avoiding data conversion.
 
-###Add segment with path and format
+### Add segment with path and format
 Users can add the existing data as a segment to the carbon table provided the schema of the data
  and the carbon table should be the same.
 

Review comment:
       Looks like syntax is wrong. Should be
   Alter table table_name add segment options (‘path’= 'hdfs://usr/oldtable,'format'='parquet')




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Indhumathi27 commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644499287



##########
File path: docs/addsegment-guide.md
##########
@@ -17,14 +17,14 @@
 
 # Heterogeneous format segments in carbondata
 
-###Background
+### Background
 In the industry, many users already adopted to data with different formats like ORC, Parquet, JSON, CSV etc.,  
 If users want to migrate to Carbondata for better performance or for better features then there is no direct way.
 All the existing data needs to be converted to Carbondata to migrate.  
 This solution works out if the existing data is less, what if the existing data is more?  
 Heterogeneous format segments aims to solve this problem by avoiding data conversion.
 
-###Add segment with path and format
+### Add segment with path and format
 Users can add the existing data as a segment to the carbon table provided the schema of the data
  and the carbon table should be the same.
 

Review comment:
       Looks like syntax is wrong. Should be
   Alter table table_name add segment options (‘path’= 'hdfs://usr/oldtable','format'='parquet')




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Indhumathi27 commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644499287



##########
File path: docs/addsegment-guide.md
##########
@@ -17,14 +17,14 @@
 
 # Heterogeneous format segments in carbondata
 
-###Background
+### Background
 In the industry, many users already adopted to data with different formats like ORC, Parquet, JSON, CSV etc.,  
 If users want to migrate to Carbondata for better performance or for better features then there is no direct way.
 All the existing data needs to be converted to Carbondata to migrate.  
 This solution works out if the existing data is less, what if the existing data is more?  
 Heterogeneous format segments aims to solve this problem by avoiding data conversion.
 
-###Add segment with path and format
+### Add segment with path and format
 Users can add the existing data as a segment to the carbon table provided the schema of the data
  and the carbon table should be the same.
 

Review comment:
       Looks like syntax is wrong. Should be
   Alter table table_name add segment options ('path'= 'hdfs://usr/oldtable','format'='parquet')




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Indhumathi27 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853586410


   @maheshrajus Still, one testclass is missed. Check DeleteCarbonTableTestCase


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maheshrajus commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644519936



##########
File path: docs/addsegment-guide.md
##########
@@ -37,12 +37,12 @@ In the above command user can add the existing data to the carbon table as a new
 During add segment, it will infer the schema from data and validates the schema against the carbon table.
 If the schema doesn’t match it throws an exception.
 
-###Changes to tablestatus file
+### Changes to tablestatus file

Review comment:
       done




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maheshrajus commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644520527



##########
File path: docs/addsegment-guide.md
##########
@@ -51,7 +51,7 @@ To support multiple formats per segment basis we can create multiple RDD using t
 Note: This integration will be clean as we use the sparks optimized reading, pruning and it

Review comment:
       done




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maheshrajus commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644521186



##########
File path: docs/addsegment-guide.md
##########
@@ -17,14 +17,14 @@
 
 # Heterogeneous format segments in carbondata
 
-###Background
+### Background
 In the industry, many users already adopted to data with different formats like ORC, Parquet, JSON, CSV etc.,  
 If users want to migrate to Carbondata for better performance or for better features then there is no direct way.
 All the existing data needs to be converted to Carbondata to migrate.  
 This solution works out if the existing data is less, what if the existing data is more?  
 Heterogeneous format segments aims to solve this problem by avoiding data conversion.
 
-###Add segment with path and format
+### Add segment with path and format
 Users can add the existing data as a segment to the carbon table provided the schema of the data
  and the carbon table should be the same.
 

Review comment:
       done




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Indhumathi27 removed a comment on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853586410


   @maheshrajus Still, one testclass is missed. Check DeleteCarbonTableTestCase


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853678609


   Build Failed  with Spark 2.4.5, Please check CI http://121.244.95.60:12602/job/ApacheCarbon_PR_Builder_2.4.5/3737/
   


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853683198


   Build Failed  with Spark 2.3.4, Please check CI http://121.244.95.60:12602/job/ApacheCarbonPRBuilder2.3/5481/
   


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maheshrajus commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853750909


   retest this please


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853804617


   Build Failed  with Spark 2.3.4, Please check CI http://121.244.95.60:12602/job/ApacheCarbonPRBuilder2.3/5486/
   


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maheshrajus commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853805660


   retest this please


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853806090


   Build Success with Spark 2.4.5, Please check CI http://121.244.95.60:12602/job/ApacheCarbon_PR_Builder_2.4.5/3742/
   


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Indhumathi27 commented on a change in pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#discussion_r644722715



##########
File path: docs/addsegment-guide.md
##########
@@ -17,41 +17,41 @@
 
 # Heterogeneous format segments in carbondata
 
-###Background
+### Background
 In the industry, many users already adopted to data with different formats like ORC, Parquet, JSON, CSV etc.,  
 If users want to migrate to Carbondata for better performance or for better features then there is no direct way.
 All the existing data needs to be converted to Carbondata to migrate.  
 This solution works out if the existing data is less, what if the existing data is more?  
 Heterogeneous format segments aims to solve this problem by avoiding data conversion.
 
-###Add segment with path and format
+### Add segment with path and format
 Users can add the existing data as a segment to the carbon table provided the schema of the data
  and the carbon table should be the same.
 
 ```
-Alter table table_name add segment options (‘path’= 'hdfs://usr/oldtable,'format'=parquet)
+alter table table_name add segment options ('path'= 'hdfs://usr/oldtable','format'='parquet')
 ```
 In the above command user can add the existing data to the carbon table as a new segment and also
  can provide the data format.
 
 During add segment, it will infer the schema from data and validates the schema against the carbon table.
 If the schema doesn’t match it throws an exception.
 
-###Changes to tablestatus file
-Carbon adds the new segment by adding segment information to tablestatus file. In order to add the path and format information to tablestatus, we are going to add `segmentPath`  and ‘format’  to the tablestatus file.
+### Changes to tablestatus file
+Carbon adds the new segment by adding segment information to tablestatus file. In order to add the path and format information to tablestatus, we are going to add `segmentPath`  and format  to the tablestatus file.

Review comment:
       ```suggestion
   Carbon adds the new segment by adding segment information to tablestatus file. In order to add the path and format information to tablestatus, we are going to add `segmentPath`  and `format`  to the tablestatus file.
   ```




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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853868751


   Build Success with Spark 2.4.5, Please check CI http://121.244.95.60:12602/job/ApacheCarbon_PR_Builder_2.4.5/3746/
   


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CarbonDataQA2 commented on pull request #4140:
URL: https://github.com/apache/carbondata/pull/4140#issuecomment-853872379


   Build Failed  with Spark 2.3.4, Please check CI http://121.244.95.60:12602/job/ApacheCarbonPRBuilder2.3/5490/
   


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