How does the stream table work?
Once a stream has formed, they draw the stream, noting locations where erosion and deposition have occurred. Then, they take measurements of the stream channel and stream flow in order to calculate velocity, sinuosity, gradient, and discharge.
What is Streamtable in hive?
In Hive, we can optimize a query by using STREAMTABLE hint. We can specify it in SELECT query with JOIN. During the map/reduce stage of JOIN, a table data can be streamed by using this hint.
What is default join in hive?
1 Answer. Hive supports equi joins by default. You can optimize your join by using Map-side Join or a Merge Join depending upon the size and sort order of your tables.
How do I use inner join in hive?
How to Perform Joins in Apache Hive
- INNER JOIN – Select records that have matching values in both tables.
- LEFT JOIN (LEFT OUTER JOIN) – Returns all the values from the left table, plus the matched values from the right table, or NULL in case of no matching join predicate.
What is anti join in hive?
“Anti” means that we don’t really join the right hand side, we only check if a join would NOT yield results for any given tuple.
What are anti join?
Anti-join between two tables returns rows from the first table where no matches are found in the second table. It is opposite of a semi-join. An anti-join returns one copy of each row in the first table for which no match is found. Anti-joins are written using the NOT EXISTS or NOT IN constructs.
What is Mapjoin?
Mapjoin is a little-known feature of Hive. It allows a table to be loaded into memory so that a (very fast) join could be performed entirely within a mapper without having to use a Map/Reduce step. It directs Hive to load aliasname (which is a table or alias of the query) into memory.
Which MapReduce join is generally faster?
Whereas the Reduce side join can join both the large data sets. The Map side join is faster as it does not have to wait for all mappers to complete as in case of reducer. Hence reduce side join is slower.
What is reduce side join?
What is Reduce Side Join? As discussed earlier, the reduce side join is a process where the join operation is performed in the reducer phase. Basically, the reduce side join takes place in the following manner: Mapper reads the input data which are to be combined based on common column or join key.
What is Mapside join?
Working of Map Side Join in Hive. Although even if queries frequently depend on small table joins, usage of map joins speed up queries’ execution. Moreover, it is the type of join where a smaller table is loaded into memory and the join is done in the map phase of the MapReduce job.
How do you optimize a join in hive?
optimize. bucketmapjoin=true; before the query. If the tables don’t meet the conditions, Hive will simply perform the normal Inner Join. If both tables have the same amount of buckets and the data is sorted by the bucket keys, Hive can perform the faster Sort-Merge Join.
What is the input to the reduce function?
The Reduce function also takes inputs as pairs, and produces pairs as output.
What is the benefit of MAP side join?
Advantages of using map side join: Map-side join helps in minimizing the cost that is incurred for sorting and merging in the shuffle and reduce stages. Map-side join also helps in improving the performance of the task by decreasing the time to finish the task.
Which operation would do a global ordering of data in the final reducer?
ORDER BY x : guarantees global ordering, but does this by pushing all data through just one reducer. This is basically unacceptable for large datasets. You end up one sorted file as output. SORT BY x : orders data at each of N reducers, but each reducer can receive overlapping ranges of data.
How do you join 2 files on map side in a MapReduce job?
How to Join two DataSets: MapReduce Example
- Input: The input data set is a txt file, DeptName.txt & DepStrength.txt.
- Step 2) Uncompress the Zip File sudo tar -xvf MapReduceJoin.tar.gz.
- Step 3) Go to directory MapReduceJoin/ cd MapReduceJoin/
What is the max size of map side join small table?
Although By default, the maximum size of a table to be used in a map join (as the small table) is 1,000,000,000 bytes (about 1 GB), you can increase this manually also by hive set properties example: set hive.
What is Bucket map join in hive?
In Hive, Bucket map join is used when the joining tables are large and are bucketed on the join column. In this kind of join, one table should have buckets in multiples of the number of buckets in another table. It means that only the matching buckets of small tables are replicated onto each mapper while joining.
Which type of join should be used when both the tables are larger in size?
Reduce-Side Join in Hadoop To join 2 large tables all rows are shuffled i.e. moved from all data nodes to reducer nodes where the actual join is performed.
What are joins in hive in MapReduce paradigm?
Hive joins are executed by MapReduce jobs through different execution engines like for example Tez, Spark or MapReduce. Joins even of multiple tables can be achieved by one job only. Since it’s first release many optimizations have been added to Hive giving users various options for query improvements of joins.
Is Hadoop good for Joins?
Joins find maximum usage in Hadoop processing. They should be used when large data sets are encountered and there is no urgency to generate the outcome. In case of Hadoop common joins, Hadoop distributes all the rows on all the nodes based on the join key.
How do 2 reducers communicate with each other?
Every task instance has its own JVM process. For every new task instance, a JVM process is spawned by default for a task. 17) Can reducers communicate with each other? Reducers always run in isolation and they can never communicate with each other as per the Hadoop MapReduce programming paradigm.
How many types of joins are there?
five types
What is the most common type of join?
The most common type of join is: SQL INNER JOIN (simple join). An SQL INNER JOIN returns all rows from multiple tables where the join condition is met.