I am working on a situation where I want to store my data in pig script into a file. This is pretty straight forward to do that, but I want file name to be derived from the data itself. So, I have a field in data as timestamp. I want to use say MAX(timestamp) as filename to store all the data for that day.
I know the usage of
STORE data INTO '$outputDir' USING org.apache.pig.piggybank.storage.MultiStorage('$outputDir', '2', 'none', ',');
But this variable "outputDir should be passed as the parameter. I want to set this value with a derived value of the field.
Any pointers will be really helpful.
Thanks & Regards,
Atul Aggarwal
In MultiStorage you specify a root directory because typically a HDFS installation is shared by many users, so you do not want data written anywhere. Hence you cannot change the root directory but you can specify which field is used to generate directory names within that directory (in your case 2). The Javadoc is helpful but I am guessing you have seen that already?
Related
I'm currently working on DataStage IBM and here's my problem:
I have to get a n numbers of datasets that's going to be in a folder and I have to append them in one DataSet (.ds).
Since I don't know how many datasets I will have and neither they full name, I can't use a DataStage job to deal with them. All I know is they will have the same metadata (because they will be generated in the same job).
I think I have to use a Shell Cmd to append them but I'm not a UNIX guy.
Thank you for everyone who reads so far.
You can use the same job. Specify Append mode (rather than Override) for the target Data Set; each time you run the job data will be added to the same Data Set. Be careful not to inadvertently create duplicates by processing the same source data twice. Use parameters to specify the source.
I'am new to Spark, Hadoop and all what comes with. My global need is to build a real-time application that get tweets and store them on HDFS in order to build a report based on HBase.
I'd like to get the generated filename when calling saveAsTextFile RRD method in order to import it to Hive.
Feel free to ask for further informations and thanks in advance.
saveAsTextFile will create a directory of sequence files. So if you give it path "hdfs://user/NAME/saveLocation", a folder called saveLocation will be created filled with sequence files. You should be able to load this into HBase simply by passing the directory name to HBase (sequenced files are a standard in Hadoop).
I do recommend you look into saving as a parquet though, they are much more useful than standard text files.
From what I understand, You saved your tweets to hdfs and now want the file names of those saved files. Correct me if I'm wrong
val filenames=sc.textfile("Your hdfs location where you saved your tweets").map(_._1)
This gives you an array of rdd's into filenames onto which you could do your operations. Im a newbie too to hadoop, but anyways...hope that helps
We started with a bunch of data stored in NetCDF files. From there, some Java code was written to create sequence files from the NetCDF files. We don't know much about the original intentions of the code, but we have been able to learn a little bit about the sequence files themselves. Ultimately, we are trying to create tables within Hive using these sequence files, but seem incapable of doing so at the moment.
We know that the keys and values within the sequence files are stored as objects that implements WritableComparable. We are also capable of creating Java code to iterate through all of the data in the sequence files.
So, what would be necessary to actually get Hive to read the data within the objects of these sequence files properly?
Thanks in advanced!
UPDATE: The reason it is so difficult to describe where I am having trouble exactly is because I am not necessarily getting any errors. Hive is simply just reading the sequence files incorrectly. When running the Hadoop -text command on my sequence file I get a list of objects as such:
NetCDFCompositeKey#263c7e3f , NetCDFRecordWritable#4d846db5
The data is within those objects themselves. So, currently from the help of #Tariq I believe what I have to do in order to actually read those objects is to create a custom InputFormat to read the keys and a custom SerDe to serialize and deserialize the objects?
I'm sorry, i'm not able to understand from your question where exactly you are facing the problem. If you wish to use SequenceFiles through Hive you just have to add STORED AS SEQUENCEFILE clause while issuing CREATE TABLE(most probably you already know this, nothing new). When you work on SequenceFiles Hive treats each key/value pair of the SequenceFiles similar to rows in normal files. Important thing here is that keys will be ignored. Apart from that nothing very special.
Having said that, if you wish to read both keys and values, you might have to write a custom InputFormat that can read both keys and values. See this project for example. It allows us to access data stored in a SequenceFile's key.
Also, if your keys and values are custom classes, you will require to write a SerDe as well to serialize and deserialize your data.
HTH
P.S. : I don't know if this is exactly what you were looking for. Do let me know if it is not and add some more detail to your question. I'll try addressing that.
how to work on specific part of cvs file uploaded into HDFS ?
I'm new in Hadoop and i have an a question that is if i export an a relational database into cvs file then uploaded it into HDFS . so how to work on specific part (table) in file using MapReduce .
thanks in advance .
I assume that the RDBMS tables are exported to individual csv files for each table and stored in HDFS. I presume that, you are referring to column(s) data within the table(s) when you mentioned 'specific part (table)'. If so, place the individual csv files into the separate file paths say /user/userName/dbName/tables/table1.csv
Now, you can configure the job for the input path and field occurrences. You may consider to use the default Input Format so that your mapper would get one line at time as input. Based on the configuration/properties, you can read the specific fields and process the data.
Cascading allows you to get started very quickly with MapReduce. It has framework that allows you to set up Taps to access sources (your CSV file) and process it inside a pipeline say to (for example) add column A to column B and place the sum into column C by selecting them as Fields
use BigTable means convert your database to one big table
I've got this file containing a list of data in Hadoop. I've build a simple Pig script which analyze the file by the id number, and so on...
The last step I'm looking for is this: I'd like to to create (store) a file for each unique id number. So this should depend on a group step...however, I haven't understood if this is possible (maybe there is a custom store module?).
Any idea?
Thanks
Daniele
While keeping in mind what is said by frail, MultiStorage, in PiggyBank, seems to be what you are looking for.
for getting an output(file or anything) you need to assign data to a variable, thats how it works with STORE. If id's are limited and finite you can FILTER them one by one and then STORE them. (I always do that for action types which is about 20-25).
But if you need to get each unique id file badly then make 2 files. 1 with whole data in it grouped by id, 1 with just unique ids. Then try generating 1(or more if you have too many) pig scripts that FILTER BY that id. But it's a bad solution. Assuming you would group 10 ids in a pig script you would have (unique id count/10) pig scripts to run.
Beware that Hdfs ain't good at handling too many small files.
Edit:
A better solution would be to GROUP and SORT by unique id to a big file. Then since its sorted you can easily divide the contents with a 3rd party script.