Table of Contents
How does HDFS handle data replication?
Data Replication. HDFS is designed to reliably store very large files across machines in a large cluster. It stores each file as a sequence of blocks; all blocks in a file except the last block are the same size. It periodically receives a Heartbeat and a Blockreport from each of the DataNodes in the cluster.
Can we modify data in HDFS?
You can not modified data once stored in hdfs because hdfs follows Write Once Read Many model. You can only append the data once stored in hdfs.
Why is HDFS only suitable for large data sets and not the correct tool for many small files?
HDFS is more efficient for a large number of data sets, maintained in a single file as compared to the small chunks of data stored in multiple files. In simple words, more files will generate more metadata, that will, in turn, require more memory (RAM).
Where is HDFS replication controlled?
You can check the replication factor from the hdfs-site. xml fie from conf/ directory of the Hadoop installation directory. hdfs-site. xml configuration file is used to control the HDFS replication factor.
How do I change the replication factor in HDFS?
For changing the replication factor across the cluster (permanently), you can follow the following steps:
- Connect to the Ambari web URL.
- Click on the HDFS tab on the left.
- Click on the config tab.
- Under “General,” change the value of “Block Replication”
- Now, restart the HDFS services.
What is HDFS fsck?
HDFS fsck is used to check the health of the file system, to find missing files, over replicated, under replicated and corrupted blocks.
What is replication factor in big data?
What Is Replication Factor? Replication factor dictates how many copies of a block should be kept in your cluster. The replication factor is 3 by default and hence any file you create in HDFS will have a replication factor of 3 and each block from the file will be copied to 3 different nodes in your cluster.
How do I update hive?
Update records in a partitioned Hive table :
- The main table is assumed to be partitioned by some key.
- Load the incremental data (the data to be updated) to a staging table partitioned with the same keys as the main table.
- Join the two tables (main & staging tables) using a LEFT OUTER JOIN operation as below:
Can multiple clients write into an HDFS file concurrently?
Can multiple clients write into an HDFS file concurrently? No, multiple clients cannot write into an HDFS file at same time. When one client is given permission by Name node to write data on data node block, the block gets locked till the write operations is completed.