Reading COW Table Views

Reading the real-time view (using Hive and SparkSQL as an example): Directly read the Hudi table stored in Hive.
```
select count(*) from test;
```

Reading the real-time view (using the Spark DataSource API as an example): This is similar to reading a common DataSource table.

QUERY_TYPE_OPT_KEY must be set to QUERY_TYPE_SNAPSHOT_OPT_VAL.

spark.read.format("hudi")
.option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_SNAPSHOT_OPT_VAL) // Set the query type to the real-time view.
.load("/tmp/default/cow_bugx/*/*/*/*") // Set the path of the Hudi table to be read. The current table has three levels of partitions.
.createTempView("mycall")
spark.sql("select * from mycall").show(100)

Reading the incremental view (using Hive and SparkSQL as an example):

set hoodie.test.consume.mode=INCREMENTAL;  // Specify the incremental reading mode.
set hoodie.test.consume.max.commits=3;  // Specify the maximum number of commits to be consumed.
set hoodie.test.consume.start.timestamp=20201227153030;  // Specify the initial incremental pull commit.
select count(*) from default.test where `_hoodie_commit_time`>'20201227153030'; // This filtering condition must be added, and the value is the initial incremental pull commit.

Reading the incremental view (using the Spark DataSource API as an example):

QUERY_TYPE_OPT_KEY must be set to QUERY_TYPE_INCREMENTAL_OPT_VAL.

spark.read.format("hudi")  
.option(QUERY_TYPE_OPT_KEY, QUERY_TYPE_INCREMENTAL_OPT_VAL) // Set the query type to the incremental mode.
.option(BEGIN_INSTANTTIME_OPT_KEY, "20210308212004")  // Specify the initial incremental pull commit.
.option(END_INSTANTTIME_OPT_KEY, "20210308212318")  //: Specify the end commit of the incremental pull.
.load("/tmp/default/cow_bugx/*/*/*/*")  // Set the path of the Hudi table to be read. The current table has three levels of partitions.
.createTempView("mycall")  // Register as a Spark temporary table.
spark.sql("select * from mycall where `_hoodie_commit_time`>'20210308211131'")// Start the query. The statement is the same as the Hive incremental query statement.
.show(100, false)