Rahul & Aaron, I will take a look at the alternate approach of having different clusters. Sounds like a very promising method.
I have another question related to BlurPartitioner. I assume that rowId and it's data resides in only one shard. Is this correct? In that case, how to handle a single-shard that become too unwieldy over a period of time? [serving too much data and/or too many rowIds]. What are your suggestions. -- Ravi On Tue, Sep 24, 2013 at 6:36 AM, Aaron McCurry <[email protected]> wrote: > Ravi, > > See my comments below. > > On Mon, Sep 23, 2013 at 8:48 AM, Ravikumar Govindarajan < > [email protected]> wrote: > > > Rahul, > > > > "When a search request is issued to the Blur Controller it searches > > though all the shard servers in parallel and each shard server searches > > through all of its shards. > > Unlike database partitioning, I believe we cannot direct a search to > a > > particular shard. > > However > > 1. Upon shard server start, all the shards are warmed up ie Index > > Reader's for each shard is loaded into memory > > 2. Blur uses a block level cache. With sufficient memory > allocated > > to the cache, performance will be greatly enhanced" > > > > You are spot-on that what I was referring was a DB-Sharding like > technique > > and it definitely has some advantages, at least in our set-up. > > > > I think, what it translates in Blur, is to create N identical tables and > > maintain user-wise mappings in our app. > > > > I mean lets say I create a table for every 10k users. I will end up with > > 300 tables for 3 million users. What are the problems you foresee with > that > > large number of tables? I know for sure some K-V stores prohibit such an > > approach. > > > > I think that this is valid approach, however I wouldn't optimize too soon. > I think the performance will likely be better with one larger table (or at > least fewer) than hundreds of smaller tables. However if you need to split > into separate tables there is a feature in Blur that you will likely be > interested in using. > > In Blur the controllers act as a gateway/router for the shard cluster. > However they can access more than just a single shard cluster. If you > name each shard cluster a different name (blur-site.properties file) the > controllers see all of them and make all the tables accessible through the > controller cluster. > > For example: > > Given: > > Shard Cluster A (100 servers) 10 tables > Shard Cluster B (100 servers) 10 tables > Shard Cluster C (100 servers) 10 tables > Shard Cluster D (100 servers) 10 tables > > The controllers would present all 40 tables to the clients. I have > normally used this feature to do full replacements of MapReduced indexes > onto a off cluster while another was presenting the data users were > accessing. Once the indexing was complete the application was soft > switched to use the new table. > > Just some more ideas to think about. > > Aaron > > > > > > > -- > > Ravi > > > > > > On Thu, Sep 19, 2013 at 11:16 PM, rahul challapalli < > > [email protected]> wrote: > > > > > I will attempt to answer some of your questions below. Aaron or someone > > > else can correct me if I am wrong > > > > > > > > > On Thu, Sep 19, 2013 at 6:15 AM, Ravikumar Govindarajan < > > > [email protected]> wrote: > > > > > > > Thanks Aaron. I think, it has answered my question. I have a few more > > and > > > > would be great if you can clarify them > > > > > > > > 1. Is the number of shards per-table fixed during table-creation or > we > > > can > > > > dynamically allocate shards? > > > > > > > > > > I believe we cannot dynamically allocate shards. The only thing we > can > > > dynamically add to an existing table is new columns > > > > > > > > > > > 2. Assuming I have 10k shards with each shard-size=2GB, for a total > of > > 20 > > > > TB table size. I typically use RowId = UserId and there are approx 3 > > > > million users, in our system > > > > > > > > How do I ensure that when a user issues a query, I should not > > end-up > > > > searching all these 10k shards, but rather search only a very small > set > > > of > > > > shards? > > > > > > > > > > When a search request is issued to the Blur Controller it searches > > > though all the shard servers in parallel and each shard server searches > > > through all of its shards. > > > Unlike database partitioning, I believe we cannot direct a search > to > > a > > > particular shard. > > > However > > > 1. Upon shard server start, all the shards are warmed up ie > Index > > > Reader's for each shard is loaded into memory > > > 2. Blur uses a block level cache. With sufficient memory > > allocated > > > to the cache, performance will be greatly enhanced > > > > > > > > > > > > > > 3. Are there any advantages of running shard-server and data-nodes > > {HDFS} > > > > in the same machine? > > > > > > > > Someone else can provide a better answer here. > > > In a typical Hadoop installation Task Trackers and Data Nodes run > > > alongside each other on the same machine. Since data nodes store the > > first > > > block replica on the > > > same machine, shard servers might see an advantage in terms of > > network > > > latency. However I think it is not a good idea to run Blur alongside > Task > > > Trackers for > > > performance reasons > > > > > > > > > > > > > -- > > > > Ravi > > > > > > > > > > > > On Thu, Sep 19, 2013 at 2:36 AM, Aaron McCurry <[email protected]> > > > wrote: > > > > > > > > > I will attempt to answer below: > > > > > > > > > > On Wed, Sep 18, 2013 at 1:54 AM, Ravikumar Govindarajan < > > > > > [email protected]> wrote: > > > > > > > > > > > Thanks a bunch for a concise and quick reply. Few more questions > > > > > > > > > > > > 1. Any pointers/links on how you plan to tackle the availability > > > > problem? > > > > > > > > > > > > Lets say we store-forward hints to the failed shard-server. Won't > > the > > > > > HDFS > > > > > > index-files differ in shard replicas? > > > > > > > > > > > > > > > > I am in the process of documenting the strategy and will be adding > it > > > to > > > > > JIRA soon. The way I am planning on solving this problem doesn't > > > involve > > > > > storing the indexes in more than once in HDFS (which of course is > > > > > replicated). > > > > > > > > > > > > > > > > > > > > > > 2. I did not phrase my question on cross-join correctly. Let me > > > clarify > > > > > > > > > > > > RowKey = 123 > > > > > > > > > > > > RecId = 1000 > > > > > > Family = "ACCOUNTS" > > > > > > Col-Name = "NAME" > > > > > > Col-Value = "ABC" > > > > > > ...... > > > > > > > > > > > > RecId = 1001 > > > > > > Family = "CONTACTS" > > > > > > Col-Name = "NAME" > > > > > > Col-Value = "XYZ" > > > > > > Col-Name = "ACCOUNTS-NAME" [FK to RecId=1000] > > > > > > Col-Value = "1000" > > > > > > ....... > > > > > > > > > > > > Lets say the user specifies the search query as > > > > > > key=123 AND name:(ABC OR XYZ) > > > > > > > > > > > > Initially I will apply this query to each of the Family types, > > namely > > > > > > "ACCOUNTS", "CONTACTS" etc.... and get their RecIds.. > > > > > > > > > > > > After this, I will have to filter "CONTACTS" family results, > based > > on > > > > > > RecIds received from "ACCOUNTS" [Join within records of different > > > > family, > > > > > > based on FK] > > > > > > > > > > > > Is something like this achievable? Can I design it differently to > > > > satisfy > > > > > > my requirements? > > > > > > > > > > > > > > > > I may not fully understand your scenario. > > > > > > > > > > As I understand your example above: > > > > > > > > > > Row { > > > > > "id" => "123", > > > > > "records" => [ > > > > > Record { > > > > > "recordId" => "1000", "family" => "accounts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > }, > > > > > Record { > > > > > "recordId" => "1001", "family" => "contacts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > } > > > > > ] > > > > > } > > > > > > > > > > Let me go through some example queries that we support: > > > > > > > > > > +<accounts.name:abc> +<contacts.name:abc> > > > > > > > > > > Another way of writing it would be: > > > > > > > > > > <accounts.name:abc> AND <contacts.name:abc> > > > > > > > > > > Would yield a hit on the Row, there aren't any FKs in Blur. > > > > > > > > > > However if there are some interesting queries that be done with > more > > > > > examples: > > > > > > > > > > Row { > > > > > "id" => "123", > > > > > "records" => [ > > > > > Record { > > > > > "recordId" => "1000", "family" => "accounts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > }, > > > > > Record { > > > > > "recordId" => "1001", "family" => "contacts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > } > > > > > ] > > > > > } > > > > > > > > > > Row { > > > > > "id" => "456", > > > > > "records" => [ > > > > > Record { > > > > > "recordId" => "1000", "family" => "accounts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > }, > > > > > Record { > > > > > "recordId" => "1001", "family" => "contacts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > }, > > > > > Record { > > > > > "recordId" => "1002", "family" => "contacts", > > > > > "columns" => [Column {"name" => "def"}] > > > > > } > > > > > ] > > > > > } > > > > > > > > > > > > > > > Row { > > > > > "id" => "789", > > > > > "records" => [ > > > > > Record { > > > > > "recordId" => "1000", "family" => "accounts", > > > > > "columns" => [Column {"name" => "abc"}] > > > > > }, > > > > > Record { > > > > > "recordId" => "1002", "family" => "contacts", > > > > > "columns" => [Column {"name" => "def"}] > > > > > } > > > > > ] > > > > > } > > > > > > > > > > For the given query: "<accounts.name:abc> AND <contacts.name:abc>" > > > would > > > > > yield 2 Row hits. 123 and 456 > > > > > For the given query: "<accounts.name:abc> AND <contacts.name:def>" > > > would > > > > > yield 2 Row hits. 456 and 789 > > > > > For the given query: "<contacts.name:abc> AND <contacts.name:def>" > > > would > > > > > yield 1 Row hit of 456. NOTICE that the family is the same here > > > > > "contacts". > > > > > > > > > > Also in Blur you can turn off the Row query and just query the > > records. > > > > > This would be your typical Document like access. > > > > > > > > > > I fear that this has not answered your question, so if it hasn't > > please > > > > let > > > > > me know. > > > > > > > > > > Thanks! > > > > > > > > > > Aaron > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > Ravi > > > > > > > > > > > > > > > > > > > > > > > > On Tue, Sep 17, 2013 at 7:01 PM, Aaron McCurry < > [email protected] > > > > > > > > wrote: > > > > > > > > > > > > > First off let me say welcome! Hopefully I can answer your > > > questions > > > > > > inline > > > > > > > below. > > > > > > > > > > > > > > > > > > > > > On Tue, Sep 17, 2013 at 6:52 AM, Ravikumar Govindarajan < > > > > > > > [email protected]> wrote: > > > > > > > > > > > > > > > I am quite new to Blur and need some help with the following > > > > > questions > > > > > > > > > > > > > > > > 1. Lets say I have a replication_factor=3 for all HDFS > indexes. > > > In > > > > > case > > > > > > > one > > > > > > > > of the server hosting HDFS indexes goes down [temporary or > > > > > take-down], > > > > > > > what > > > > > > > > will happen to writes? Some kind-of HintedHandoff [as in > > > Cassandra] > > > > > is > > > > > > > > supported? > > > > > > > > > > > > > > > > > > > > > > When there is a Blur Shard Server failure state in ZooKeeper > will > > > > > change > > > > > > > and the other shard servers will take action to bring the down > > > > shard(s) > > > > > > > online. This is similar to the HBase region model. While the > > > > shard(s) > > > > > > are > > > > > > > being relocated (which really means being reopened from HDFS) > > > writes > > > > to > > > > > > the > > > > > > > shard(s) being moved are not available. However the bulk load > > > > > capability > > > > > > > is always available as long as HDFS is available, this can be > > used > > > > > > through > > > > > > > Hadoop MapReduce. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > To re-phrase, what is the Consistency Vs Availability > trade-off > > > in > > > > > > Blur, > > > > > > > > with replication_factor>1 for HDFS indexes? > > > > > > > > > > > > > > > > > > > > > > Of the two Consistency is favored over Availability, however we > > are > > > > > > > starting development (in 0.3.0) to increase availability during > > > > > failures. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > 2. Since HDFSInputStream is used underneath, will this result > > in > > > > too > > > > > > much > > > > > > > > of data-transfer back-and-forth? A case of > multi-segment-merge > > or > > > > > even > > > > > > > > wild-card search could trigger it. > > > > > > > > > > > > > > > > > > > > > > Blur uses an in process file system cache (Block Cache is the > > term > > > > used > > > > > > in > > > > > > > the code) to reduce the IO from HDFS. During index merges data > > > that > > > > is > > > > > > not > > > > > > > in the Block Cache is read from HDFS and the output is written > > back > > > > to > > > > > > > HDFS. Overall once an index is hot (been online for some time) > > the > > > > IO > > > > > > for > > > > > > > any given search is fairly small assuming that the cluster has > > > enough > > > > > > > memory configured in the Block Cache. > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > 3. Does Blur also support foreign-key like semantics to > search > > > > across > > > > > > > > column-families as well as delete using row_id? > > > > > > > > > > > > > > > > > > > > > > Blur supports something called Row Queries that allow for > > searches > > > > > across > > > > > > > column families within single Rows. Take a look at this page > > for a > > > > > > better > > > > > > > explanation: > > > > > > > > > > > > > > > > > http://incubator.apache.org/blur/docs/0.2.0/data-model.html#querying > > > > > > > > > > > > > > And yes Blur supports deletes by Row check out: > > > > > > > > > > > > > > > > > http://incubator.apache.org/blur/docs/0.2.0/Blur.html#Fn_Blur_mutate > > > > > > > and > > > > > > > > > > > > > > > > http://incubator.apache.org/blur/docs/0.2.0/Blur.html#Struct_RowMutation > > > > > > > > > > > > > > Hopefully this can answer so of your questions. Let us know if > > you > > > > > have > > > > > > > any more. > > > > > > > > > > > > > > Thanks, > > > > > > > Aaron > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > -- > > > > > > > > Ravi > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > > >
