generated by map and reduce · Hive.merge.mapfiles = True if and Map output file, default to True· Hive.merge.mapredfiles = False if the Reduce output file is merged, the default is False· Hive.merge.size.per.task = 256*1000*1000 the size of the merged file five, in/exists (not) implements the in operation through the left semi join, and one restriction is that the table to the right of the join can only appear in the join bar Part VI, partition clipping by specifying a partition in the crite
eliminate this impact:
· Hive. Merge. mapfiles = true: whether to merge with the map output file. The default value is true.
· Hive. Merge. mapredfiles = false: whether to merge reduce output files. The default value is false.
· Hive. Merge. Size. Per. Task = 256*1000*1000 size of the merged FileIv. Hive implementatio
Hive Query Optimization Summary
Storage, learning, sharing one, join optimization
The basic principle of join lookup operations: You should place a table/subquery with fewer entries on the left side of the join operator. The reason is that in the reduce phase of the join operation, the contents of the table on the le
Query statements can reduce the number of partitions that are read by placing the "subq.prtn=100" condition in a subquery more efficient. Hive automatically performs this cropping optimization.
Partition parameter is: hive.optimize.pruner=true (default value is True)
Add: The actual cluster operation process, plus partitioning is the most importa
the serialization and deserialization of data Io, the main function of which is to parse the HDFs file and identify the format. Some of the early Hive-serde packages have been discarded, the latest documents refer to the "Official Serde-wiki", and the hive-supported built-in Serde is as follows, and the following are all available after we upgrade to hive1.0. Avro (Hiv
6.1 SELECT ... From statementhive> SELECT name,salary from employees;--General Queryhive>select e.name, e.salary from Employees e;--alias query is also supported when a user selects a column that is a collection data type, Hive uses JSON syntax to apply to the output:hive> SELECT name,subordinates from employees;Display of the array type of John Doe ["Mary Smith", "Todd Jones"]
viii. Query Statement select for hive
In all database systems, the SELECT statement is the most used, but also the most complex piece, the query in hive Select support syntax is certainly more complex, this article only try to introduce. 8.1 Basic Query Syntax
The Select ba
′);10) Load DFS data with a given partition informationLOAD DATA inpath '/user/myname/kv2.txt ' OVERWRITE into TABLE invites PARTITION (ds= ' 2008-08-15′);11) Output the query results to a local directory fileINSERT OVERWRITE LOCAL DIRECTORY '/tmp/local_out ' SELECT a.* from pokes A;12) Create an index for the tableCreate an index for table UserloginlogCREATE index Index_user_login_log on table Userloginlog (userid) as ' Org.apache.hadoop.hive.ql.inde
num) method. This method can be used to increase the number of map tasks, but the number of tasks can not be set less than the Hadoop system by dividing the input data obtained by the value. Of course, in order to improve the concurrency of the cluster, you can set a default number of maps, when the user's map number is small or more than the self-segmentation of the value of the hour can use a relatively large default value, thereby improving the efficiency of the overall Hadoop cluster.Hive
join generates a temporary table then the T5, then union all, becomes 2 jobs. Insert Overwrite Table T5 Select * from T2 joins t3 on t2.id = t3.id; Select * FROM (T1 UNION all T4 Union All T5); Hive can do more intelligently on union all optimization (as a query as a temporary table), which can reduce the burden on developers. The reason for this problem should
kinds of contradictions, one is to merge small files, one is to take large files into small files, this is the focus of attention, this is the place toaccording to the actual situation, the control map quantity needs to follow two principle: Make the Big Data quantity use the appropriate map number, make the individual map task handle the appropriate data quantity;For more details, please follow the Superman Academy: Bj-crxyThis article from "Superman College" blog, reproduced please contact th
Hive is a data Warehouse tool based on Hadoop that maps structured data files to a database table and provides a simple SQL query that translates SQL statements into MapReduce tasks.
Metastore (hive meta data)Hive stores metadata in a database, such as MySQL, Derby. The metadata in
invalidates the optimization of the Union all execution plan of hive.
If you have a better optimization solution, please leave a message to us.8. refer:
 hive query-joining two tables on three joining conditions with or operator
Hive optimization tips-How to Write HQL
I. Hive join Optimization1. try to place the small table on the left of join. The hive-0.12.0 we use here is automatically converted. This means that the small table is automatically loaded into the memory and the map side join is executed (with good performance ), this is done b
when optimizing, hive SQL as a map reduce program to read, there will be unexpected surprises.
Understanding the core competencies of Hadoop is fundamental to hive optimization. This is a valuable experience summary for all members of the project team over the past year.
Long-term observations of Hadoop process data have several notable features :
1. Not afrai
when the same field is joined consecutively. Select * from a left Outer Join B on. T = B. T left Outer Join C on. T = C. t; Recommended select * from a left Outer Join B on. T = B. T left Outer Join C on B. T = C. t; inefficient
6. when a large table and a small table are joined, mapjoin is used to read small tables into memory for join, select/* + mapjoin (a) */. c1, B. c2, B. c3 from a join B on. c4 = B. c4;
7. By setting hive. Merge. mapfiles, you
1.hive Fuzzy Search Table
Show tables like ' *name* ';2. View table structure InformationDESC formatted table_name;DESC table_name;3. View partition informationShow partitions table_name;4. Querying data based on partitionsSelect Table_coulm from table_name where partition_name = ' 2017-02-25 ';5. View HDFs File informationDFS-LS/USER/HIVE/WAREHOUSE/TABLE02;6. Load data into table from file (overwrite overw
Hive ive optimization essentials:
When optimizing, hive SQL as a map reduce program to read, there will be unexpected surprises.
Understanding the core competencies of Hadoop is fundamental to hive optimization. Long-term observations of Hadoop process data have several nota
. Optimization of orderby sort by distribute
The sorting keyword of hive is sort by, which is intentionally different from the order by of traditional databases to emphasize the difference between the two-sort by can only be sorted within the Single Machine range.
Set mapred. Reduce. Tasks = 2; (set the reduce quantity to 2)
1. selectcookie_id, page_id, ID from c02_clickstat_fat
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