[DISCUSSION] About the future of hive integration

[cenyuhai11]

Hi, community:

    The purpose I create the module "hive integration" is not just making carbondata available to query in hive. I want carbondata to be a common fileformat in hadoop ecosystem like orc、parquet.

    In hadoop ecosystem, the common fileformat in data warehouse  are orc、parquet.  For my company, we have thousands of orc tables.

    Can carbondata become a common fileformat? I think yes!

   Hive is slow, but hive is widely used, stable and hive metastore has become a industrial standard in fact.

    Follow the behavior of hive will help us easier to change the existed tables to carbondata and will not use double storage. Just like the usage described in jira: https://issues.apache.org/jira/browse/CARBONDATA-1377.

    The detailed things we can do in Carbondata 1.3.0 are as below:

    1. File Level OutputFormat https://issues.apache.org/jira/browse/CARBONDATA-729 

    2. Hive partition https://issues.apache.org/jira/browse/CARBONDATA-1377

    3. Improve batch query performance, query without index should be as faster as parquet (In my test, query without index is slower than parquet, It is blocked by initializing tasks)

    4. Improve the time to load the index, it is too slow for the first time

    If there are omissions, please add.

    My imagination, What do you think?

    

    

Best regards!

Yuhai Cen

[cenyuhai11]

Best regards!

Yuhai Cen

在2017年10月15日 13:25，[hidden email] 写道：

Hi, community:

    The purpose I create the module "hive integration" is not just making carbondata available to query in hive. I want carbondata to be a common fileformat in hadoop ecosystem like orc、parquet.

    In hadoop ecosystem, the common fileformat in data warehouse  are orc、parquet.  For my company, we have thousands of orc tables.

    Can carbondata become a common fileformat? I think yes!

   Hive is slow, but hive is widely used, stable and hive metastore has become a industrial standard in fact.

    Follow the behavior of hive will help us easier to change the existed tables to carbondata and will not use double storage. Just like the usage described in jira: https://issues.apache.org/jira/browse/CARBONDATA-1377.

    The detailed things we can do in Carbondata 1.3.0 are as below:

    1. File Level OutputFormat https://issues.apache.org/jira/browse/CARBONDATA-729 

    2. Hive partition https://issues.apache.org/jira/browse/CARBONDATA-1377

    3. Improve batch query performance, query without index should be as faster as parquet (In my test, query without index is slower than parquet, It is blocked by initializing tasks)

    4. Improve the time to load the index, it is too slow for the first time

    If there are omissions, please add.

    My imagination, What do you think?

    

    

Best regards!

Yuhai Cen

[cenyuhai]

Hi, community:

    The purpose I create the module "hive integration" is not just making carbondata available to query in hive. I want carbondata to be a common fileformat in hadoop ecosystem like orc、parquet.

    In hadoop ecosystem, the common fileformat in data warehouse  are orc、parquet.  For my company, we have thousands of orc tables.

    Can carbondata become a common fileformat? I think yes!

    Hive is slow, but hive is widely used, stable and hive metastore has become a industrial standard in fact.

     Follow the behavior of hive will help us easier to change the existed tables to carbondata and will not use double storage. Just like the usage described in jira: https://issues.apache.org/jira/browse/CARBONDATA-1377.

     The detailed things we can do in Carbondata 1.3.0 are as below:

     1. File Level OutputFormat https://issues.apache.org/jira/browse/CARBONDATA-729 

     2. Hive partition https://issues.apache.org/jira/browse/CARBONDATA-1377

    3. Improve batch query performance, query without index should be as faster as parquet (In my test, query without index is slower than parquet, It is blocked by initializing tasks)

    4. Improve the time to load the index, it is too slow for the first time

    If there are omissions, please add.

    My imagination, What do you think?

   

   

Best regards!

Yuhai Cen