Im curious how do recovery softwares open the Master File Table. Like do they do api calls ?
There are no API calls to read an MFT. But you can find the cluster where the Mft is stored and read its content by traversing through disk.
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I've been using services like Kafka Connect and Secor to persist Parquet files to S3. I'm not very familiar with HDFS or Hadoop but it seems like these services typically write temporary files either into local memory or to disk before writing in bulk to s3. Do the s3n/s3a file systems virtualize an HDFS-style file system locally and then push at configured intervals or is there a one-to-one correspondence between a write to s3n/s3a and a write to s3?
I'm not entirely sure if I'm asking the right question here. Any guidance would be appreciated.
S3A/S3N just implement the Hadoop FileSystem APIs against the remote object store, including pretending it has directories you can rename and delete.
They have historically saved all the data you write to the local disk until you close() the output stream, at which point the upload takes place (which can be slow). This means that you must have as much temporary space as the biggest object you plan to create.
Hadoop 2.8 has a fast upload stream which uploads the file in 5+MB blocks as it gets written, then in the final close() makes it visible in the object store. This is measurably faster when generating lots of data in a single stream. This also avoids needing so much disk space.
I want to transfer Un-semi structured data(MS word/PDF/JSON) from a remote computer into hadoop(could be in batch and could be near realtime but not stream).
I have to Make sure that data is moved quickly from Remote location to my local machine(working on low bandwidth)into HDFS or local machine.
Fro example Internet Download Manager has this amazing technique of making several connections with the FTP and utilizing low bandwidth with more connections.
Is there any possibility that Hadoop ecosystem provides such a tool to ingest data into hadoop. Or any self made technique?
Which Tool/Technique could be better.
You could use the Web HDFS API http://hadoop.apache.org/docs/current/hadoop-project-dist/hadoop-hdfs/WebHDFS.html#Document_Conventions
I am not able to find a specific link that explains to me how the meta data is distributed in MAPR(File meta data). When I look at cloudera / hortonworks /apache hadoop I know the meta data is stored in namenode's memory which is then fetched to locate the nodes that holds the blocks. How does it work in MAPR is what I am trying to understand.
Any help would be greatly appreciated.
MapR natively implemented a Network File System (NFS) interface to MapR-FS so that any reads and writes from and to a file system, whether it be to a local file system, Network Attached Storage, or a Storage Area Network, can read and write data from and to MapR-FS.
This is also the reason MapR asks for a raw disk during the installation so that, it reformats the disk as MapR-FS.
Just came across this thread :
http://answers.mapr.com/questions/108/how-is-metadata-stored.html
I have this erratic client who wants to push data from HAWQ to GREENPLUM after some pre processing. Is there any way to do this? If not, Is it possible to create an external table in greenplum that reads it from the HDFS in which HAWQ is running?
Any help will be appreciated.
The simplest you can do - push the data from HAWQ to HDFS using external writable table and then read it from Greenplum using external readable table using gphdfs protocol. In my opinion this would be the fastest option.
Another option would be to store the data in gzipped CSV files on HDFS and work with them directly from HAWQ. This way when you need this data in Greenplum you can just query it in the same way, as an external table
HAWQ is same as Greenplum, only underlying storage is hdfs,
One way is You can create a externale(writable) table in HAWQ which will write your data into a file, now after this you can create a external(readable) table in Greenplum which will read data from that created file
Another way You can copy from one server to another using Standard Input/Output, I use it many times when required to puch data from development environment to Prodcution or vice-versa
Another way You can table a backup using pg_dump/gp_dump for particular table/tables then restore using pg_restore/gp_restore
Thanks
I would like to understand does hadoop support for siebel applications , can any body share experience in doing that. I looked for online documentation and not able to find any proper link to explain this so posting question here
I have and siebel application run with Oracle database, I would like to replace with HAdoop ..is it possible ?
No is the answer.
Basically Hadoop isn't a database at all.
Hadoop is basically a distributed file system (HDFS) - it lets you store large amount of file data on a cloud of machines, handling data redundancy etc.
On top of that distributed file system it provides an API for processing all stored data using something called as Map-Reduce.