Thanks Pete! So far it looks good on my end: I can use my event logging framework to store the events to HDFS, run vanilla MapReduce jobs on them (using SerDe to deserialize the thrift to java objects) and keep the possibility to use Hive in the future. I'm also interested to try out Pigs (I might need to implement some glue from serde to pigs, but I believe that's easy). But I still have one question remaining:
I'm currently storing (I just got the storing code ready this afternoon) the events in Sequence files with timestamp as the key and thrift serialized bytecode (as BytesWritable) as the value. One file will contain one hour worth of data. So for one day I'll have 24 different files. Also each file is placed into a subdirectory which contains one week files (identified by week number). So todays files will be placed under "/events/thrift/MyThriftStuctureName/36/". Can Hive understand this type of data partitioning? Should I change this partitioning, or can I create some class which makes hive to understand this with a little effort? So far Hive looks a good way to solve some of our problems, but I'll want to wait at least for hadoop 0.19.0 release (which should have Hive included). But I also want to start collecting the data right now and to keep my system ready to easily support hive in the future. Thanks, - Juho Mäkinen On Wed, Sep 3, 2008 at 8:30 PM, Pete Wyckoff <[EMAIL PROTECTED]> wrote: > > Hi Juho, > > Excellent - yes, we do something very similar using Thrift, Scribe (our soon > to be open sourced logging framework) and SerDes. > > The SerDe is a uniform interface to data for serialization and > deserialization. If you look at the interface, it provides 4 methods - > serialize, deserialize and 2 methods to query the type information. It > supports Thrift, Jute, and control delimited data and can be easily > extended to support things like ProtocolBuffers. > > So, Hive doesn't care about the actual data format in HDFS although its > default native serialization for Text data is control separated. > > For thrift, you could use ThriftSerDe passing in a Properties object to its > initializer that includes the name of the thrift class it is representing. > In Hive, we use the Hive Metastore to store this information so the runtime > just passes the name of the "table" to the MS which returns the information > needed to instantiate the SerDe. > > We are interested, however, in integrating with > https://issues.apache.org/jira/browse/HADOOP-3787, but we haven't looked at > this much yet. > > Thanks, pete > > > On 9/3/08 12:32 AM, "Juho Mäkinen" <[EMAIL PROTECTED]> wrote: > >> Thanks Jeff. I believe that you mean the serde module inside hadoop >> (hadoop-core-trunk\src\contrib\hive\serde)? >> I'm currently looking into it, but it seems to lack a lot of useful >> documentation so it'll take me some time to figure it out (all >> additional info is appreciated). >> >> I've already put some effort into this and designed a partial >> sollution for my log analysis which so far seems ok to me. As I don't >> know the details of serde yet, I'm not sure if this is the way I >> should go, or should I change my implementation and plans so that I >> could use serve (if it makes my job easier). I'm not yet interested in >> HIVE, but I'd like to keep the option open in the future, so that I >> could easily run hive on my datas (so that I would not need to >> transform my datas to hive if I choose to use it in the future). >> >> Currently I've come up with the following design: >> 1) Each log event type has it's own thrift structure. The structure is >> compiled into php code. The log entry creators creates and populates >> the structure php object with data and sends it to be stored >> 2) Log sender object receiveres this object ($tbase) and serializes it >> using TBinaryTransport, adds the structure name to the beginning and >> sends the byte array to loc receiver using UDP. The following code >> does this: >> >> $this->transport = new TResetableMemoryBuffer(); // a TMemoryBuffer >> with a reset() method >> $this->protocol = new TBinaryProtocol($this->transport); >> $this->transport->open(); >> >> $this->transport->reset(); // Reset the memory buffer array >> $this->protocol->writeByte(1); // version 1: we have the TBase name in string >> $this->protocol->writeString($tbase->getName()); // Name of the structure >> $tbase->write($this->protocol); // Serialize our thrift structure to >> the memory buffer >> >> $this->sendBytes($this->transport->getBuffer()); >> >> 3) Log receiver reads the structure name and stores the byte array >> (without the version byte and structure name) into HDFS file >> "/events/<insert structure name here>/<week >> number>/<timestamp>.datafile" >> >> My plan is that I could read the stored entries using MapReduce, >> deserialize them into java objects (the map-reducer would need to have >> the thrift compiled structures available) and use the structures >> directly in Map operations. (How) can serde help me with this part? >> Should I modify my plans so that I could use HIVE directly in the >> future? How Hive stores the thrift serialized log data into HDFS? >> >> - Juho Mäkinen >> >> On Wed, Sep 3, 2008 at 7:37 AM, Jeff Hammerbacher >> <[EMAIL PROTECTED]> wrote: >>> Hey Juho, >>> >>> You should check out Hive >>> (https://issues.apache.org/jira/browse/HADOOP-3601), which was just >>> committed to the Hadoop trunk today. It's what we use at Facebook to >>> query our collection of Thrift-serialized logfiles. Inside of the Hive >>> code, you'll find a pure-Java (using JavaCC) parser for >>> Thrift-serialized data structures. >>> >>> Regards, >>> Jeff >>> >>> On Tue, Sep 2, 2008 at 6:57 AM, Stuart Sierra <[EMAIL PROTECTED]> wrote: >>>> On Tue, Sep 2, 2008 at 3:53 AM, Juho Mäkinen <[EMAIL PROTECTED]> wrote: >>>>> What's the current status of Thrift with Hadoop? Is there any >>>>> documentation online or even some code in the SVN which I could look >>>>> into? >>>> >>>> I think you have two choices: 1) wrap your Thrift code in a class that >>>> implements Writable, or 2) use Thrift to serialize your data to byte >>>> arrays and store them as BytesWritable. >>>> -Stuart
