邏輯和物理計劃如何工作時讀蜂巢分區表在獸人pyspark dataframe嗎
emp_df = spark.read.format("com.databricks.spark.csv") \
.option("mode", "DROPMALFORMED") \
.option("header", "true") \
.option("inferschema", "true") \
.option("delimiter", ",").load(PATH_TO_FILE)
emp_df.repartition(5, ‘emp_id‘).write.format(‘orc‘).partitionBy("emp_id").saveAsTable("UDB.temptable")
當我閱讀此表如下方法如果我看看邏輯和物理計劃,似乎它已經完全過濾的數據使用分區鍵列:
emp_df_1 = spark.sql("select * from UDB.temptable where emp_id =‘6‘")
emp_df_1.explain(True)
== Parsed Logical Plan ==
‘Project [*]
+- ‘Filter (‘emp_id = 6)
+- ‘UnresolvedRelation UDB.temptable
== Analyzed Logical Plan ==
emp_name: string, emp_city: string, emp_salary: int, emp_id: int
Project [emp_name#7399, emp_city#7400, emp_salary#7401, emp_id#7402]
+- Filter (emp_id#7402 = cast(6 as int))
+- SubqueryAlias temptable
== Optimized Logical Plan ==
Filter (isnotnull(emp_id#7402) && (emp_id#7402 = 6))
+- Relation[emp_name#7399,emp_city#7400,emp_salary#7401,emp_id#7402] orc
== Physical Plan ==
*(1) FileScan orc udb.temptable[emp_name#7399,emp_city#7400,emp_salary#7401,emp_id#7402] Batched: true, Format: ORC, Location: PrunedInMemoryFileIndex[hdfs://pathlocation/database/udb....,
PartitionCount: 1, PartitionFilters: [isnotnull(emp_id#7402), (emp_id#7402 = 6)], PushedFilters: [], ReadSchema: struct<emp_name:string,emp_city:string,emp_salary:int>
而如果我讀這個dataframe通過絕對hdfs路徑位置,似乎不能夠過濾數據使用分區鍵列:
emp_df_2 = spark.read.format("orc").load("hdfs://pathlocation/database/udb.db/temptable/emp_id=6")
emp_df_2.explain(True)
== Parsed Logical Plan ==
Relation[emp_name#7411,emp_city#7412,emp_salary#7413] orc
== Analyzed Logical Plan ==
emp_name: string, emp_city: string, emp_salary: int
Relation[emp_name#7411,emp_city#7412,emp_salary#7413] orc
== Optimized Logical Plan ==
Relation[emp_name#7411,emp_city#7412,emp_salary#7413] orc
== Physical Plan ==
*(1) FileScan orc [emp_name#7411,emp_city#7412,emp_salary#7413] Batched: true, Format: ORC, Location: InMemoryFileIndex[hdfs://pathlocation/data/database/udb.db/tem...,
PartitionFilters: [], PushedFilters: [], ReadSchema: struct<emp_name:string,emp_city:string,emp_salary:int>
你能幫我了解邏輯和物理計劃的情況下?
邏輯和物理計劃如何工作時讀蜂巢分區表在獸人pyspark dataframe嗎