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https://issues.apache.org/jira/browse/HUDI-1307?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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sivabalan narayanan updated HUDI-1307:
--------------------------------------
    Component/s: reader-core

> spark datasource load path format is confused for snapshot and increment read 
> mode
> ----------------------------------------------------------------------------------
>
>                 Key: HUDI-1307
>                 URL: https://issues.apache.org/jira/browse/HUDI-1307
>             Project: Apache Hudi
>          Issue Type: Improvement
>          Components: reader-core, spark
>            Reporter: liwei
>            Assignee: liwei
>            Priority: Critical
>              Labels: query-eng, sev:high, user-support-issues
>
> as spark datasource read hudi table
> 1、snapshot mode
> {code:java}
>  val readHudi = spark.read.format("org.apache.hudi").load(basePath + "/*");
> should add "/*" ,otherwise will fail, because in 
> org.apache.hudi.DefaultSource.
> createRelation() will use fs.globStatus(). if do not have "/*" will not get 
> .hoodie and default dir
> val globPaths = HoodieSparkUtils.checkAndGlobPathIfNecessary(allPaths, 
> fs){code}
>  
> 2、increment mode
> both basePath and  basePath + "/*"  is ok.This is because in 
> org.apache.hudi.DefaultSource  
> DataSourceUtils.getTablePath can support both the two format.
> {code:java}
>  val incViewDF = spark.read.format("org.apache.hudi").
>  option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL).
>  option(BEGIN_INSTANTTIME_OPT_KEY, beginTime).
>  option(END_INSTANTTIME_OPT_KEY, endTime).
>  load(basePath){code}
>  
> {code:java}
>  val incViewDF = spark.read.format("org.apache.hudi").
>  option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL).
>  option(BEGIN_INSTANTTIME_OPT_KEY, beginTime).
>  option(END_INSTANTTIME_OPT_KEY, endTime).
>  load(basePath + "/*")
>  {code}
>  
> as  increment mode and snapshot mode not coincide, user will confuse .Also 
> load use basepath +"/*"  *or "/***/*"* is  confuse. I know this is to support 
> partition.
> but i think this api will more clear for user
>  
> {code:java}
>  partition = "year = '2019'"
> spark.read .format("hudi") .load(path) .where(partition) {code}
>  
>  ```



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