Spark 分区修剪在 1.6.0 上不起作用

Question

我在 hdfs 上创建了分区 parquet 文件并创建了 HIVE 外部表。当我在分区列上使用过滤器查询表时，spark 检查所有分区文件而不是特定分区。我们正在使用 Spark 1.6.0。

数据框：

   df = hivecontext.createDataFrame([
    ("class1", "Economics", "name1", None),
    ("class2","Economics", "name2", 92),
    ("class2","CS", "name2", 92),
    ("class1","CS", "name1", 92)
], ["class","subject", "name", "marks"])

创建镶木地板分区：

hivecontext.setConf("spark.sql.parquet.compression.codec", "snappy")
hivecontext.setConf("spark.sql.hive.convertMetastoreParquet", "false")
df1.write.parquet("/transient/testing/students", mode="overwrite", partitionBy='subject')

查询：

df = hivecontext.sql('select * from vatmatching_stage.students where subject = "Economics"')
df.show()

+------+-----+-----+---------+
| class| name|marks|  subject|
+------+-----+-----+---------+
|class1|name1|    0|Economics|
|class2|name2|   92|Economics|
+------+-----+-----+---------+

df.explain(True)

    == Parsed Logical Plan ==
    'Project [unresolvedalias(*)]
    +- 'Filter ('subject = Economics)
       +- 'UnresolvedRelation `vatmatching_stage`.`students`, None

    == Analyzed Logical Plan ==
    class: string, name: string, marks: bigint, subject: string
    Project [class#90,name#91,marks#92L,subject#89]
    +- Filter (subject#89 = Economics)
       +- Subquery students
          +- Relation[class#90,name#91,marks#92L,subject#89] ParquetRelation: vatmatching_stage.students

    == Optimized Logical Plan ==
    Project [class#90,name#91,marks#92L,subject#89]
    +- Filter (subject#89 = Economics)
       +- Relation[class#90,name#91,marks#92L,subject#89] ParquetRelation: vatmatching_stage.students

    == Physical Plan ==
    Scan ParquetRelation: vatmatching_stage.students[class#90,name#91,marks#92L,subject#89] InputPaths: hdfs://dev4/transient/testing/students/subject=Art, hdfs://dev4/transient/testing/students/subject=Civil, hdfs://dev4/transient/testing/students/subject=CS, hdfs://dev4/transient/testing/students/subject=Economics, hdfs://dev4/transient/testing/students/subject=Music

但是，如果我在 HIVE 浏览器上执行相同的查询，我们可以看到 HIVE 正在执行分区修剪。

44 location hdfs://testing/students/subject=Economics
45 name vatmatching_stage.students
46 numFiles 1
47 numRows -1
48 partition_columns subject
49 partition_columns.types string

这是 spark 1.6.0 中的限制还是我在这里遗漏了什么。

Answer 1

找到了这个问题的根本原因。用于查询表的 HiveContext 没有将 spark.sql.hive.convertMetastoreParquet" 设置为 "false"。它设置为 "true" - 默认值。

当我将它设置为“false”时，我可以看到它正在使用分区修剪。