Re: SQL layer over Accumulo?

[James Taylor <ja...@apache.org>]

Thanks for the explanations, Josh. This sounds very doable. Few more
comments inline below.

James


On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com> wrote:

>
>
> On 4/30/14, 3:33 AM, James Taylor wrote:
>
>> On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
>> wrote:
>>
>>  @Josh - it's less baked in than you'd think on the client where the query
>>>
>>>> parsing, compilation, optimization, and orchestration occurs. The
>>>> client/server interaction is hidden behind the ConnectionQueryServices
>>>> interface, the scanning behind ResultIterator (in
>>>> particular ScanningResultIterator), the DML behind MutationState, and
>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
>>>> require
>>>> some more abstraction, but probably not too bad, though. On the
>>>> server-side, the entry points would all be different and that's where
>>>> I'd
>>>> need your insights for what's possible.
>>>>
>>>>
>>> Definitely. I'm a little concerned about what's expected to be provided
>>> by
>>> the "database" (HBase, Accumulo) as I believe HBase is a little more
>>> flexible in allowing writes internally where Accumulo has thus far said
>>> "you're gonna have a bad time".
>>>
>>
>>
>> Tell me more about what you mean by "allowing writes internally".
>>
>
> Haha, sorry, that was a sufficiently ominous statement with insufficient
> context.
>
> For discussion sake, let's just say HBase coprocessors and Accumulo
> iterators are equivalent, purely in the scope of "running server-side code"
> (in the RegionServer/TabletServer). However, there is a notable difference
> in the pipeline where each of those are implemented.
>
> Coprocessors have built-in hooks that let you get updates on
> PUT/GET/DELETE/etc as well as pre and post each of those operations. In
> other words, they provide hooks at a "high database level".
>
> Iterators tend to be much closer to the data itself, only dealing with
> streams of data (other iterators stacked on one another). Iterators
> implement versioning, visibilities, and can even implement complex
> searches. The downside of this approach is that iterators lack any means to
> safely write data _outside of the sorted Key-Value pairs in the tablet
> currently being processed_. It's possible to make in tablet updates, but
> sorted order within a large tablet might make this difficult as well.
>
> This is why I was thinking percolator would be a better solution, as it's
> meant for handling updates like this server-side. However, I imagine it
> would be possible, in the short-term, to make some separate process between
> Phoenix and Accumulo which handles writes.


Another fallback might be to do global index maintenance on the client.
It'd just be more expensive, especially if you want to handle out-of-order
updates (which are particularly tricky, as you have to get multiple
versions of the rows to work out all the different scenarios here).

A second fallback might be to support only local indexing. Does Accumulo
have the concept of a "custom load balancer" that would allow you to
co-locate two regions from different tables? The local-index features has
kind of driven some feature requests on that front for HBase - mainly
callbacks when a region is split or re-located. The rows of the local index
are prefixed with the region start key to keep them together and identify
them.

>
>
>
>>
>>>
>>>   @Eric - I agree about having txn support (probably through snapshot
>>>
>>>> isolation) by controlling the timestamp, and then layering indexing on
>>>> top
>>>> of that. That's where we're headed. But I wouldn't let that stop the
>>>> effort
>>>> - it would just be layered on top of what's already there. FWIW, there's
>>>> another interesting indexing model that has been termed "local
>>>> indexing"(
>>>> https://github.com/Huawei-Hadoop/hindex) which is being worked on right
>>>> now
>>>> (should be available in either our 4.1 or 4.2 release). In this model,
>>>> the
>>>> table data and index data are co-located on the same region server
>>>> through
>>>> a kind of "buddy" region mechanism. The advantage is that you take no
>>>> hit
>>>> at write time, as you're writing both the index and table data together.
>>>> Not sure how/if this would transfer over to the Accumulo world.
>>>>
>>>>
>>> Interesting. Given that Accumulo doesn't have a fixed column family
>>> schema, this might make index generation even easier (maybe "cleaner" is
>>> the proper word). You could easily co-locate the indices with the data,
>>> given them a proper name.
>>>
>>>
>> With HBase, you can do something similar (though, you're right, you'd need
>> to create the column family upfront or take the hit of creating it
>> dynamically - that's a nice feature that Accumulo has). The reason this
>> doesn't work is that you need a different row key so that the index rows
>> are ordered according to their indexed column values. If you put it in a
>> column family of the data table, they're ordered in the same way as the
>> data table. This makes range scans over index tables very expensive, as
>> the
>> rows would need to be re-ordered.
>>
>>
> Ah, of course. You need the term up front to make it sort properly.
>
>
>
>>> Problem still exists that we don't have a solid way to do this solely
>>> inside of Accumulo ATM. I'd imagine that if someone stepped up to
>>> implement
>>> coprocessors, we'd be taking the route of a separate, standalone process
>>> (as opposed to in-RegionServer). Hypothetically, we could do the same for
>>> Phoenix in the short-term.
>>>
>>> Can you quantify what would be expected by Accumulo to integrate with
>>> Phoenix (maybe list what exactly is done inside of HBase at a high
>>> level?)
>>> so that we could give some more targeted ideas/feelings as to what the
>>> level of work would be inside Accumulo?
>>>
>>
>>
>> There's not a lot of hard/fast requirements. Most of what Phoenix does is
>> to optimize performance by leveraging the capabilities of the server. In
>> terms of hard/fast requirements, these come to mind:
>> - data is returned in row key order from range scans
>> - a scan may set a start key/stop key to do a range scan
>> - a row key may be composed of arbitrary bytes
>> - a client may "pre-split" a table by providing the region boundaries at
>> table create time (we rely on this for salting to prevent hotspotting:
>> http://phoenix.incubator.apache.org/salted.html).
>> - the client has access to the region boundaries of a table (this allows
>> for better parallelization)
>> - the client may issue chunk up a scan into smaller, multiple scans and
>> run
>> them in parallel
>> Some of these may be a bit squishy, as there may be existing machinery
>> already in your client programming model that could be leverage. The
>> client
>> API of HBase, for example, does not provide the ability out of the box to
>> parallelize a scan, so this is something Phoenix had to add on top
>> (through
>> chunking up scans at or within region boundaries).
>>
>
> All of these look fine. The Accumulo BatchScanner does that
> parallelization for you which is really nice (handling tablet migration and
> all that fun stuff transparently).


That's nice that Accumulo has this built-in. Does it allow the client to
specify the split points for the scan in some way?

>
>
>
>  Phoenix manages the metadata of your tables (tables, columns, indexes,
>> views, etc) in an HBase table. DDL statements such as CREATE TABLE, DROP
>> TABLE, ALTER TABLE are atomic, transactional operations b/c we don't want
>> our metadata table to get in a corrupt state. To accomplish this, we rely
>> on:
>> - setting a "split policy" that ensures that the table data for a given
>> "tenant" (we support multi-tenancy:
>> http://phoenix.incubator.apache.org/multi-tenancy.html) stay together in
>> the same region.
>> - putting the data using an API that guarantees that either the entire
>> batch of mutations succeed or fail completely.
>> Again, these are details of our implementation on HBase which do not
>> necessarily need to be implemented in the same way on a different system.
>>
>
> I'd have to look again at how our mutation failures are handled (or
> someone else can chime in). This might be something to keep an eye on
> depending on the distribution of mutations in regards to tables.
>
>
>  Phoenix supports sequences which are atomically incremented values. This
>> is
>> done through a coprocessor currently, due to some limitations with the
>> HBase Increment API, but the idea is the same as an atomic increment.
>>
>
> Conditional Mutations in the about-to-be-released version 1.6.0 will
> provide this.
>
>
>  Phoenix does the following push down:
>> - the WHERE clause gets transformed into three things: a start/stop key of
>> a scan, a skip scan filter to efficiently navigate the key space (see
>> http://phoenix-hbase.blogspot.com/2013/05/demystifying-skip-
>> scan-in-phoenix.html),
>> and a custom filter to rule out a row based on some java code that does
>> expression evaluation.
>> - the GROUP BY clause gets pushed to the server and a coprocessor runs the
>> scan on each region so that the client doesn't have to get back all the
>> raw
>> data. Instead, the client gets back the aggregated data (to conserve
>> network bandwidth and to run the scan where the data lives). The client
>> then does a final merge sort.
>>
>
> I've written an iterator to do a group by previously. Depending on the
> schema this is fine.
>
>
>  - the ORDER BY clause used in combination with the LIMIT clause is a TopN
>> query. We optimize this by each region holding on to the top N values with
>> the client then doing a merge sort with the limit applied.
>>
>
> This is an interesting one. If you remove the possibility of tablets
> splitting out from underneath you and you had a view of the splits, you
> could probably pull it off.
>
>
>  - the ORDER BY clause on it's own gets executed on each region (spooled
>> using memory mapped files) and then the client does a merge sort. This
>> spooling could potentially be done on the client side.
>>
>
> Unless we can do some trickery with the schema, yeah, client side.
>
>
>  - joins are executed as a broadcast hash join. We run one side of the
>> query
>> (with the filters applied), compact the results, and send them to each
>> region server where they are cached while we run the other side of the
>> query. A coprocessor then does a map lookup (equi-joins only are supported
>> currently) to join based on the join key and returns the joined results
>> (i.e. the concatenated values in a single, condensed key value as access
>> from the client is positional post-join).
>>
>
> The join approach would need to be implemented some other way for the
> earlier stated comparison of iterators and coprocessors.


Client-side could be another fallback. The coprocessor approach is really
only a big win in two cases: if you have a join which doesn't have many
matches (as those rows get filtered on the server-side), or for correlated
sub queries or exists queries where you can filter or collapse many rows to
one or none on the server-side rather than return them all to the client.

>
>
>  For our global secondary indexes (local secondary indexes are different as
>> we discussed already), we trap updates to the data table through a
>> coprocessor. For index maintenance you need to know when a change occurs
>> to
>> a data row what the prior value of the row was. The reason is because you
>> need to delete the index row corresponding to the old data row and then
>> insert the index row corresponding to the new value (remember, the index
>> value makes up the row key). By doing this operation through a
>> coprocessor,
>> we know that we can get the prior data row state locally. We still need to
>> issue a Put from one region server to another, but this isn't really an
>> extra hop, as if it was done on the client, the same hop would need to be
>> done (but the old row state would need to be pulled over to the client
>> which is not necessary with the coprocessor based approach). For more on
>> global secondary indexing, see
>> http://phoenix.incubator.apache.org/secondary_indexing.html (there are
>> some
>> good presentations at the end of the page that provide more technical
>> detail).
>>
>
> Right, you want to remove the old index value and update a new index value
> (actually being two unique keys) in the same transaction to ensure a valid
> index. Or, at least ensure that you never remove the old value, and die
> before inserting the new value.
>
> Again, not going to work well in an iterator.
>
>
>  Phoenix also allows "point-in-time" queries where a client may establish a
>> connection at an earlier timestamp. If your table is setup to keep
>> multiple
>> versions of the same row, then you can query "back-in-time" and will see
>> the data as it was at that point. We more or less get this for free with
>> the MVCC model of HBase by specifying a max timestamp on a scan. One
>> slightly tricky bit is we correlate the current DDL of your table based on
>> the same timestamp as with your data. So when you go back-in-time like
>> this, you'll also see the structure of your table as it was at time also.
>>
>
> I don't see this as a problem. As long as we remove the versioning
> iterator from a table (which keeps the most recent version of a key by
> default), it should be pretty easy to implement an iterator which adheres
> to the "max timestamp" semantics.
>
>
>  So we do rely on coprocessors, but the underlying APIs were accessing on
>> the server-side are pretty light.
>>
>>   TLDR? Let's continue in the JIRA?
>>
>>>
>>>>
>>> Mailing list is fine by me for while we get this hashed out :). We can
>>> move to Jira when we start getting into specifics.
>>>
>>>
>>

Re: SQL layer over Accumulo?

[James Taylor <ja...@apache.org>]

That sounds promising, Josh & William. Is there a performance penalty with
this approach (versus traversing the rows in row key order)?
Thanks,
James


On Fri, May 16, 2014 at 8:27 AM, Josh Elser <jo...@gmail.com> wrote:

> On 5/11/14, 12:22 AM, James Taylor wrote:
>
>> @William - it's entirely possible that my HBase terminology is not mapping
>> well to Accumulo terminology. If Accumulo has a capability not present in
>> HBase that'll handle this, that'd be great.
>>
>> In HBase terminology, by row I mean all of the key values across all
>> column
>> families with the same row key (Row ID in Accumulo?). So in HBase, it
>> doesn't work to store the index data in a separate column family for the
>> same row, because the rows are ordered according to the data table row
>> key.
>> We need the rows of an index to be ordered by the row key formed by the
>> indexed columns instead. Otherwise we have to re-sort the rows which is
>> more expensive than just doing a scan over the data table.
>>
>
> (sorry for the delay, still trying to stay on top of mail from the outage)
>
> I think I know what Bill is trying to get at here and it hinges on the
> fact that Accumulo doesn't require you to define the column families for a
> table up front (it has a default locality group which all colfams which
> don't have a locality group defined go into -- differs from HBase where
> locality group == colfam).
>
> Because of this, you can use the column family and qualifier to get the
> properly sorting index records instead of using the row key (assuming the
> row is just some bucket/partitioning element). Thus, you can co-locate
> index and data key-values within the same row if you're tricky enough with
> how you create the table. :)
>
>
>  With buddy regions, the two regions are from different tables with
>> different row key orders. All of the data from "D" for a given region is
>> contained in the buddy region for "I", but in a different order. We
>> equally
>> rely on the buddy region for "I" being in row key order according to the
>> indexed columns (as opposed to the row key order of the data table).
>>
>> Thanks,
>> James
>>
>>
>> On Sat, May 10, 2014 at 7:21 PM, William Slacum <
>> wilhelm.von.cloud@accumulo.net> wrote:
>>
>>  So there may be a bit of confusion with storing index and data in the
>>> same
>>> row. By "row" I just mean the logical Accumulo unit, not a "row" as in
>>> "thing in my relational table." Synonyms for "row" in this scheme are
>>> "shard" and "document partition".
>>>
>>> You can store multiple documents and indices for those documents in
>>> different column families within the same row. You then have separate
>>> readers for the indices and document data ("sources" in Iterator terms).
>>> Point and range queries are still possible in this fashion, and are made
>>> even easier if there's another level that maps terms to
>>> rows/shards/partition. The wikisearch example is an (admittedly rough)
>>> implementation of this.
>>>
>>> I think looking at how "buddy" regions work may help clarify things,
>>> since
>>> I imagine it works similarly. If the coprocessor is just reading from a
>>> region "I", that that contains index data for only region "D", then that
>>> maps pretty well to an iterator scanning index data from a column family
>>> "I" and fetching documents from a column family "D".
>>>
>>>
>>>
>>> On Thu, May 8, 2014 at 1:09 AM, James Taylor <ja...@apache.org>
>>> wrote:
>>>
>>>  Sorry for the delay in getting back to you - things got a bit crazy with
>>>> our graduation and HBaseCon happening at the same time.
>>>>
>>>> @Josh & Bill - r.e. Co-locating indices within the same row simplifies
>>>>
>>> this
>>>
>>>> a bit.
>>>> The secondary indexes need to be in row key order by the indexed
>>>> columns,
>>>> so co-locating them in the data table wouldn't allow the lookup and
>>>> range
>>>> scan abilities we'd need. The advantage of the index is that you don't
>>>>
>>> need
>>>
>>>> to look at all the data, but can do a point lookup or range scan based
>>>> on
>>>> the usage of the indexed columns in a query.
>>>>
>>>> @Josh - r.e. Assuming I understand properly, you don't need to be
>>>>
>>> cognizant
>>>
>>>> of the splits. You just specify the Ranges (where each Range is a start
>>>>
>>> key
>>>
>>>> and end key) and the Accumulo client API does the rest.
>>>>
>>>> Typically the Ranges are merge sorted on the client, so this might
>>>>
>>> require
>>>
>>>> an extension to the Accumulo client.
>>>>
>>>> r.e. Next steps.
>>>>
>>>> We'd definitely need an expert on the Accumulo side to proceed. I'm
>>>> happy
>>>> to help on the Phoenix side - I'll post a note on our dev list too to
>>>> see
>>>> if there are other folks interested as well. Given the similarities
>>>>
>>> between
>>>
>>>> Accumulo and HBase and the abstraction Phoenix already has in place, I
>>>> don't think the effort would be large to get something up and running.
>>>> Maybe a phased approach, would make sense: first with query support and
>>>> next with secondary index support?
>>>>
>>>> Not sure where this stacks up in terms of priority for you all. At
>>>> Salesforce, we saw a specific need for this with HBase, the "big data
>>>> store" on top of which we'd choose to standardize. We realized early on
>>>> that we'd never get the adoption we wanted without providing a
>>>> different,
>>>> more familiar programming model: namely SQL. Since we were targeting
>>>> supporting interactive web-based applications, anything map/reduce based
>>>> wasn't a fit which led us to create Phoenix. Perhaps there are members
>>>> in
>>>> your community in the same boat?
>>>>
>>>> Thanks,
>>>> James
>>>>
>>>>
>>>>
>>>> On Fri, May 2, 2014 at 1:44 PM, Josh Elser <jo...@gmail.com>
>>>> wrote:
>>>>
>>>>  On 5/1/14, 2:24 AM, James Taylor wrote:
>>>>>
>>>>>  Thanks for the explanations, Josh. This sounds very doable. Few more
>>>>>> comments inline below.
>>>>>>
>>>>>> James
>>>>>>
>>>>>>
>>>>>> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com>
>>>>>>
>>>>> wrote:
>>>>
>>>>>
>>>>>>
>>>>>>
>>>>>>> On 4/30/14, 3:33 AM, James Taylor wrote:
>>>>>>>
>>>>>>>   On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <josh.elser@gmail.com
>>>>>>> >
>>>>>>>
>>>>>>>> wrote:
>>>>>>>>
>>>>>>>>    @Josh - it's less baked in than you'd think on the client where
>>>>>>>>
>>>>>>> the
>>>
>>>> query
>>>>>>>>
>>>>>>>>
>>>>>>>>>   parsing, compilation, optimization, and orchestration occurs. The
>>>>>>>>>
>>>>>>>>>> client/server interaction is hidden behind the
>>>>>>>>>>
>>>>>>>>> ConnectionQueryServices
>>>>
>>>>> interface, the scanning behind ResultIterator (in
>>>>>>>>>> particular ScanningResultIterator), the DML behind MutationState,
>>>>>>>>>>
>>>>>>>>> and
>>>>
>>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
>>>>>>>>>> require
>>>>>>>>>> some more abstraction, but probably not too bad, though. On the
>>>>>>>>>> server-side, the entry points would all be different and that's
>>>>>>>>>>
>>>>>>>>> where
>>>>
>>>>> I'd
>>>>>>>>>> need your insights for what's possible.
>>>>>>>>>>
>>>>>>>>>>
>>>>>>>>>>   Definitely. I'm a little concerned about what's expected to be
>>>>>>>>>>
>>>>>>>>> provided
>>>>>>>>> by
>>>>>>>>> the "database" (HBase, Accumulo) as I believe HBase is a little
>>>>>>>>>
>>>>>>>> more
>>>
>>>> flexible in allowing writes internally where Accumulo has thus far
>>>>>>>>>
>>>>>>>> said
>>>>
>>>>> "you're gonna have a bad time".
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>
>>>>>>>> Tell me more about what you mean by "allowing writes internally".
>>>>>>>>
>>>>>>>>
>>>>>>>>  Haha, sorry, that was a sufficiently ominous statement with
>>>>>>>
>>>>>> insufficient
>>>>
>>>>> context.
>>>>>>>
>>>>>>> For discussion sake, let's just say HBase coprocessors and Accumulo
>>>>>>> iterators are equivalent, purely in the scope of "running server-side
>>>>>>> code"
>>>>>>> (in the RegionServer/TabletServer). However, there is a notable
>>>>>>> difference
>>>>>>> in the pipeline where each of those are implemented.
>>>>>>>
>>>>>>> Coprocessors have built-in hooks that let you get updates on
>>>>>>> PUT/GET/DELETE/etc as well as pre and post each of those operations.
>>>>>>>
>>>>>> In
>>>
>>>> other words, they provide hooks at a "high database level".
>>>>>>>
>>>>>>> Iterators tend to be much closer to the data itself, only dealing
>>>>>>>
>>>>>> with
>>>
>>>> streams of data (other iterators stacked on one another). Iterators
>>>>>>> implement versioning, visibilities, and can even implement complex
>>>>>>> searches. The downside of this approach is that iterators lack any
>>>>>>>
>>>>>> means
>>>>
>>>>> to
>>>>>>> safely write data _outside of the sorted Key-Value pairs in the
>>>>>>>
>>>>>> tablet
>>>
>>>> currently being processed_. It's possible to make in tablet updates,
>>>>>>>
>>>>>> but
>>>>
>>>>> sorted order within a large tablet might make this difficult as well.
>>>>>>>
>>>>>>> This is why I was thinking percolator would be a better solution, as
>>>>>>>
>>>>>> it's
>>>>
>>>>> meant for handling updates like this server-side. However, I imagine
>>>>>>>
>>>>>> it
>>>
>>>> would be possible, in the short-term, to make some separate process
>>>>>>> between
>>>>>>> Phoenix and Accumulo which handles writes.
>>>>>>>
>>>>>>>
>>>>>>
>>>>>> Another fallback might be to do global index maintenance on the
>>>>>>
>>>>> client.
>>>
>>>> It'd just be more expensive, especially if you want to handle
>>>>>>
>>>>> out-of-order
>>>>
>>>>> updates (which are particularly tricky, as you have to get multiple
>>>>>> versions of the rows to work out all the different scenarios here).
>>>>>>
>>>>>> A second fallback might be to support only local indexing. Does
>>>>>>
>>>>> Accumulo
>>>
>>>> have the concept of a "custom load balancer" that would allow you to
>>>>>> co-locate two regions from different tables? The local-index features
>>>>>>
>>>>> has
>>>>
>>>>> kind of driven some feature requests on that front for HBase - mainly
>>>>>> callbacks when a region is split or re-located. The rows of the local
>>>>>> index
>>>>>> are prefixed with the region start key to keep them together and
>>>>>>
>>>>> identify
>>>>
>>>>> them.
>>>>>>
>>>>>>
>>>>> Agreed with what Bill said. Co-locating indices within the same row
>>>>> simplifies this a bit, IMO.
>>>>>
>>>>>
>>>>> <snip/>
>>>>>
>>>>>
>>>>>
>>>>>
>>>>>>>>>
>>>>>>>> There's not a lot of hard/fast requirements. Most of what Phoenix
>>>>>>>>
>>>>>>> does
>>>
>>>> is
>>>>>>>> to optimize performance by leveraging the capabilities of the
>>>>>>>>
>>>>>>> server.
>>>
>>>> In
>>>>
>>>>> terms of hard/fast requirements, these come to mind:
>>>>>>>> - data is returned in row key order from range scans
>>>>>>>> - a scan may set a start key/stop key to do a range scan
>>>>>>>> - a row key may be composed of arbitrary bytes
>>>>>>>> - a client may "pre-split" a table by providing the region
>>>>>>>>
>>>>>>> boundaries
>>>
>>>> at
>>>>
>>>>> table create time (we rely on this for salting to prevent
>>>>>>>>
>>>>>>> hotspotting:
>>>
>>>> http://phoenix.incubator.apache.org/salted.html).
>>>>>>>> - the client has access to the region boundaries of a table (this
>>>>>>>>
>>>>>>> allows
>>>>
>>>>> for better parallelization)
>>>>>>>> - the client may issue chunk up a scan into smaller, multiple scans
>>>>>>>>
>>>>>>> and
>>>>
>>>>> run
>>>>>>>> them in parallel
>>>>>>>> Some of these may be a bit squishy, as there may be existing
>>>>>>>>
>>>>>>> machinery
>>>
>>>> already in your client programming model that could be leverage. The
>>>>>>>> client
>>>>>>>> API of HBase, for example, does not provide the ability out of the
>>>>>>>>
>>>>>>> box
>>>
>>>> to
>>>>>>>> parallelize a scan, so this is something Phoenix had to add on top
>>>>>>>> (through
>>>>>>>> chunking up scans at or within region boundaries).
>>>>>>>>
>>>>>>>>
>>>>>>>>  All of these look fine. The Accumulo BatchScanner does that
>>>>>>> parallelization for you which is really nice (handling tablet
>>>>>>>
>>>>>> migration
>>>
>>>> and
>>>>>>> all that fun stuff transparently).
>>>>>>>
>>>>>>>
>>>>>>
>>>>>> That's nice that Accumulo has this built-in. Does it allow the client
>>>>>>
>>>>> to
>>>
>>>> specify the split points for the scan in some way?
>>>>>>
>>>>>>
>>>>> Assuming I understand properly, you don't need to be cognizant of the
>>>>> splits. You just specify the Ranges (where each Range is a start key
>>>>>
>>>> and
>>>
>>>> end key) and the Accumulo client API does the rest. You can be
>>>>>
>>>> efficient
>>>
>>>> by
>>>>
>>>>> structuring your data so that you don't touch every tabletserver for
>>>>>
>>>> every
>>>>
>>>>> query -- this seems to be what's being suggested.
>>>>>
>>>>> <snip/>
>>>>>
>>>>> What do you think is next, James?
>>>>>
>>>>> I know I won't have a lot of time to devote into heavy development with
>>>>> what I've already signed up for in the next few months, but I'd still
>>>>>
>>>> like
>>>>
>>>>> to try to help out where possible. Is anyone else on the Accumulo side
>>>>> interested in getting involved?
>>>>>
>>>>>
>>>>
>>>
>>

Re: SQL layer over Accumulo?

[Josh Elser <jo...@gmail.com>]

On 5/11/14, 12:22 AM, James Taylor wrote:
> @William - it's entirely possible that my HBase terminology is not mapping
> well to Accumulo terminology. If Accumulo has a capability not present in
> HBase that'll handle this, that'd be great.
>
> In HBase terminology, by row I mean all of the key values across all column
> families with the same row key (Row ID in Accumulo?). So in HBase, it
> doesn't work to store the index data in a separate column family for the
> same row, because the rows are ordered according to the data table row key.
> We need the rows of an index to be ordered by the row key formed by the
> indexed columns instead. Otherwise we have to re-sort the rows which is
> more expensive than just doing a scan over the data table.

(sorry for the delay, still trying to stay on top of mail from the outage)

I think I know what Bill is trying to get at here and it hinges on the 
fact that Accumulo doesn't require you to define the column families for 
a table up front (it has a default locality group which all colfams 
which don't have a locality group defined go into -- differs from HBase 
where locality group == colfam).

Because of this, you can use the column family and qualifier to get the 
properly sorting index records instead of using the row key (assuming 
the row is just some bucket/partitioning element). Thus, you can 
co-locate index and data key-values within the same row if you're tricky 
enough with how you create the table. :)

> With buddy regions, the two regions are from different tables with
> different row key orders. All of the data from "D" for a given region is
> contained in the buddy region for "I", but in a different order. We equally
> rely on the buddy region for "I" being in row key order according to the
> indexed columns (as opposed to the row key order of the data table).
>
> Thanks,
> James
>
>
> On Sat, May 10, 2014 at 7:21 PM, William Slacum <
> wilhelm.von.cloud@accumulo.net> wrote:
>
>> So there may be a bit of confusion with storing index and data in the same
>> row. By "row" I just mean the logical Accumulo unit, not a "row" as in
>> "thing in my relational table." Synonyms for "row" in this scheme are
>> "shard" and "document partition".
>>
>> You can store multiple documents and indices for those documents in
>> different column families within the same row. You then have separate
>> readers for the indices and document data ("sources" in Iterator terms).
>> Point and range queries are still possible in this fashion, and are made
>> even easier if there's another level that maps terms to
>> rows/shards/partition. The wikisearch example is an (admittedly rough)
>> implementation of this.
>>
>> I think looking at how "buddy" regions work may help clarify things, since
>> I imagine it works similarly. If the coprocessor is just reading from a
>> region "I", that that contains index data for only region "D", then that
>> maps pretty well to an iterator scanning index data from a column family
>> "I" and fetching documents from a column family "D".
>>
>>
>>
>> On Thu, May 8, 2014 at 1:09 AM, James Taylor <ja...@apache.org>
>> wrote:
>>
>>> Sorry for the delay in getting back to you - things got a bit crazy with
>>> our graduation and HBaseCon happening at the same time.
>>>
>>> @Josh & Bill - r.e. Co-locating indices within the same row simplifies
>> this
>>> a bit.
>>> The secondary indexes need to be in row key order by the indexed columns,
>>> so co-locating them in the data table wouldn't allow the lookup and range
>>> scan abilities we'd need. The advantage of the index is that you don't
>> need
>>> to look at all the data, but can do a point lookup or range scan based on
>>> the usage of the indexed columns in a query.
>>>
>>> @Josh - r.e. Assuming I understand properly, you don't need to be
>> cognizant
>>> of the splits. You just specify the Ranges (where each Range is a start
>> key
>>> and end key) and the Accumulo client API does the rest.
>>>
>>> Typically the Ranges are merge sorted on the client, so this might
>> require
>>> an extension to the Accumulo client.
>>>
>>> r.e. Next steps.
>>>
>>> We'd definitely need an expert on the Accumulo side to proceed. I'm happy
>>> to help on the Phoenix side - I'll post a note on our dev list too to see
>>> if there are other folks interested as well. Given the similarities
>> between
>>> Accumulo and HBase and the abstraction Phoenix already has in place, I
>>> don't think the effort would be large to get something up and running.
>>> Maybe a phased approach, would make sense: first with query support and
>>> next with secondary index support?
>>>
>>> Not sure where this stacks up in terms of priority for you all. At
>>> Salesforce, we saw a specific need for this with HBase, the "big data
>>> store" on top of which we'd choose to standardize. We realized early on
>>> that we'd never get the adoption we wanted without providing a different,
>>> more familiar programming model: namely SQL. Since we were targeting
>>> supporting interactive web-based applications, anything map/reduce based
>>> wasn't a fit which led us to create Phoenix. Perhaps there are members in
>>> your community in the same boat?
>>>
>>> Thanks,
>>> James
>>>
>>>
>>>
>>> On Fri, May 2, 2014 at 1:44 PM, Josh Elser <jo...@gmail.com> wrote:
>>>
>>>> On 5/1/14, 2:24 AM, James Taylor wrote:
>>>>
>>>>> Thanks for the explanations, Josh. This sounds very doable. Few more
>>>>> comments inline below.
>>>>>
>>>>> James
>>>>>
>>>>>
>>>>> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com>
>>> wrote:
>>>>>
>>>>>
>>>>>>
>>>>>> On 4/30/14, 3:33 AM, James Taylor wrote:
>>>>>>
>>>>>>   On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
>>>>>>> wrote:
>>>>>>>
>>>>>>>    @Josh - it's less baked in than you'd think on the client where
>> the
>>>>>>> query
>>>>>>>
>>>>>>>>
>>>>>>>>   parsing, compilation, optimization, and orchestration occurs. The
>>>>>>>>> client/server interaction is hidden behind the
>>> ConnectionQueryServices
>>>>>>>>> interface, the scanning behind ResultIterator (in
>>>>>>>>> particular ScanningResultIterator), the DML behind MutationState,
>>> and
>>>>>>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
>>>>>>>>> require
>>>>>>>>> some more abstraction, but probably not too bad, though. On the
>>>>>>>>> server-side, the entry points would all be different and that's
>>> where
>>>>>>>>> I'd
>>>>>>>>> need your insights for what's possible.
>>>>>>>>>
>>>>>>>>>
>>>>>>>>>   Definitely. I'm a little concerned about what's expected to be
>>>>>>>> provided
>>>>>>>> by
>>>>>>>> the "database" (HBase, Accumulo) as I believe HBase is a little
>> more
>>>>>>>> flexible in allowing writes internally where Accumulo has thus far
>>> said
>>>>>>>> "you're gonna have a bad time".
>>>>>>>>
>>>>>>>>
>>>>>>>
>>>>>>> Tell me more about what you mean by "allowing writes internally".
>>>>>>>
>>>>>>>
>>>>>> Haha, sorry, that was a sufficiently ominous statement with
>>> insufficient
>>>>>> context.
>>>>>>
>>>>>> For discussion sake, let's just say HBase coprocessors and Accumulo
>>>>>> iterators are equivalent, purely in the scope of "running server-side
>>>>>> code"
>>>>>> (in the RegionServer/TabletServer). However, there is a notable
>>>>>> difference
>>>>>> in the pipeline where each of those are implemented.
>>>>>>
>>>>>> Coprocessors have built-in hooks that let you get updates on
>>>>>> PUT/GET/DELETE/etc as well as pre and post each of those operations.
>> In
>>>>>> other words, they provide hooks at a "high database level".
>>>>>>
>>>>>> Iterators tend to be much closer to the data itself, only dealing
>> with
>>>>>> streams of data (other iterators stacked on one another). Iterators
>>>>>> implement versioning, visibilities, and can even implement complex
>>>>>> searches. The downside of this approach is that iterators lack any
>>> means
>>>>>> to
>>>>>> safely write data _outside of the sorted Key-Value pairs in the
>> tablet
>>>>>> currently being processed_. It's possible to make in tablet updates,
>>> but
>>>>>> sorted order within a large tablet might make this difficult as well.
>>>>>>
>>>>>> This is why I was thinking percolator would be a better solution, as
>>> it's
>>>>>> meant for handling updates like this server-side. However, I imagine
>> it
>>>>>> would be possible, in the short-term, to make some separate process
>>>>>> between
>>>>>> Phoenix and Accumulo which handles writes.
>>>>>>
>>>>>
>>>>>
>>>>> Another fallback might be to do global index maintenance on the
>> client.
>>>>> It'd just be more expensive, especially if you want to handle
>>> out-of-order
>>>>> updates (which are particularly tricky, as you have to get multiple
>>>>> versions of the rows to work out all the different scenarios here).
>>>>>
>>>>> A second fallback might be to support only local indexing. Does
>> Accumulo
>>>>> have the concept of a "custom load balancer" that would allow you to
>>>>> co-locate two regions from different tables? The local-index features
>>> has
>>>>> kind of driven some feature requests on that front for HBase - mainly
>>>>> callbacks when a region is split or re-located. The rows of the local
>>>>> index
>>>>> are prefixed with the region start key to keep them together and
>>> identify
>>>>> them.
>>>>>
>>>>
>>>> Agreed with what Bill said. Co-locating indices within the same row
>>>> simplifies this a bit, IMO.
>>>>
>>>>
>>>> <snip/>
>>>>
>>>>
>>>>
>>>>>>>>
>>>>>>>
>>>>>>> There's not a lot of hard/fast requirements. Most of what Phoenix
>> does
>>>>>>> is
>>>>>>> to optimize performance by leveraging the capabilities of the
>> server.
>>> In
>>>>>>> terms of hard/fast requirements, these come to mind:
>>>>>>> - data is returned in row key order from range scans
>>>>>>> - a scan may set a start key/stop key to do a range scan
>>>>>>> - a row key may be composed of arbitrary bytes
>>>>>>> - a client may "pre-split" a table by providing the region
>> boundaries
>>> at
>>>>>>> table create time (we rely on this for salting to prevent
>> hotspotting:
>>>>>>> http://phoenix.incubator.apache.org/salted.html).
>>>>>>> - the client has access to the region boundaries of a table (this
>>> allows
>>>>>>> for better parallelization)
>>>>>>> - the client may issue chunk up a scan into smaller, multiple scans
>>> and
>>>>>>> run
>>>>>>> them in parallel
>>>>>>> Some of these may be a bit squishy, as there may be existing
>> machinery
>>>>>>> already in your client programming model that could be leverage. The
>>>>>>> client
>>>>>>> API of HBase, for example, does not provide the ability out of the
>> box
>>>>>>> to
>>>>>>> parallelize a scan, so this is something Phoenix had to add on top
>>>>>>> (through
>>>>>>> chunking up scans at or within region boundaries).
>>>>>>>
>>>>>>>
>>>>>> All of these look fine. The Accumulo BatchScanner does that
>>>>>> parallelization for you which is really nice (handling tablet
>> migration
>>>>>> and
>>>>>> all that fun stuff transparently).
>>>>>>
>>>>>
>>>>>
>>>>> That's nice that Accumulo has this built-in. Does it allow the client
>> to
>>>>> specify the split points for the scan in some way?
>>>>>
>>>>
>>>> Assuming I understand properly, you don't need to be cognizant of the
>>>> splits. You just specify the Ranges (where each Range is a start key
>> and
>>>> end key) and the Accumulo client API does the rest. You can be
>> efficient
>>> by
>>>> structuring your data so that you don't touch every tabletserver for
>>> every
>>>> query -- this seems to be what's being suggested.
>>>>
>>>> <snip/>
>>>>
>>>> What do you think is next, James?
>>>>
>>>> I know I won't have a lot of time to devote into heavy development with
>>>> what I've already signed up for in the next few months, but I'd still
>>> like
>>>> to try to help out where possible. Is anyone else on the Accumulo side
>>>> interested in getting involved?
>>>>
>>>
>>
>

Re: SQL layer over Accumulo?

[James Taylor <ja...@apache.org>]

@William - it's entirely possible that my HBase terminology is not mapping
well to Accumulo terminology. If Accumulo has a capability not present in
HBase that'll handle this, that'd be great.

In HBase terminology, by row I mean all of the key values across all column
families with the same row key (Row ID in Accumulo?). So in HBase, it
doesn't work to store the index data in a separate column family for the
same row, because the rows are ordered according to the data table row key.
We need the rows of an index to be ordered by the row key formed by the
indexed columns instead. Otherwise we have to re-sort the rows which is
more expensive than just doing a scan over the data table.

With buddy regions, the two regions are from different tables with
different row key orders. All of the data from "D" for a given region is
contained in the buddy region for "I", but in a different order. We equally
rely on the buddy region for "I" being in row key order according to the
indexed columns (as opposed to the row key order of the data table).

Thanks,
James


On Sat, May 10, 2014 at 7:21 PM, William Slacum <
wilhelm.von.cloud@accumulo.net> wrote:

> So there may be a bit of confusion with storing index and data in the same
> row. By "row" I just mean the logical Accumulo unit, not a "row" as in
> "thing in my relational table." Synonyms for "row" in this scheme are
> "shard" and "document partition".
>
> You can store multiple documents and indices for those documents in
> different column families within the same row. You then have separate
> readers for the indices and document data ("sources" in Iterator terms).
> Point and range queries are still possible in this fashion, and are made
> even easier if there's another level that maps terms to
> rows/shards/partition. The wikisearch example is an (admittedly rough)
> implementation of this.
>
> I think looking at how "buddy" regions work may help clarify things, since
> I imagine it works similarly. If the coprocessor is just reading from a
> region "I", that that contains index data for only region "D", then that
> maps pretty well to an iterator scanning index data from a column family
> "I" and fetching documents from a column family "D".
>
>
>
> On Thu, May 8, 2014 at 1:09 AM, James Taylor <ja...@apache.org>
> wrote:
>
> > Sorry for the delay in getting back to you - things got a bit crazy with
> > our graduation and HBaseCon happening at the same time.
> >
> > @Josh & Bill - r.e. Co-locating indices within the same row simplifies
> this
> > a bit.
> > The secondary indexes need to be in row key order by the indexed columns,
> > so co-locating them in the data table wouldn't allow the lookup and range
> > scan abilities we'd need. The advantage of the index is that you don't
> need
> > to look at all the data, but can do a point lookup or range scan based on
> > the usage of the indexed columns in a query.
> >
> > @Josh - r.e. Assuming I understand properly, you don't need to be
> cognizant
> > of the splits. You just specify the Ranges (where each Range is a start
> key
> > and end key) and the Accumulo client API does the rest.
> >
> > Typically the Ranges are merge sorted on the client, so this might
> require
> > an extension to the Accumulo client.
> >
> > r.e. Next steps.
> >
> > We'd definitely need an expert on the Accumulo side to proceed. I'm happy
> > to help on the Phoenix side - I'll post a note on our dev list too to see
> > if there are other folks interested as well. Given the similarities
> between
> > Accumulo and HBase and the abstraction Phoenix already has in place, I
> > don't think the effort would be large to get something up and running.
> > Maybe a phased approach, would make sense: first with query support and
> > next with secondary index support?
> >
> > Not sure where this stacks up in terms of priority for you all. At
> > Salesforce, we saw a specific need for this with HBase, the "big data
> > store" on top of which we'd choose to standardize. We realized early on
> > that we'd never get the adoption we wanted without providing a different,
> > more familiar programming model: namely SQL. Since we were targeting
> > supporting interactive web-based applications, anything map/reduce based
> > wasn't a fit which led us to create Phoenix. Perhaps there are members in
> > your community in the same boat?
> >
> > Thanks,
> > James
> >
> >
> >
> > On Fri, May 2, 2014 at 1:44 PM, Josh Elser <jo...@gmail.com> wrote:
> >
> > > On 5/1/14, 2:24 AM, James Taylor wrote:
> > >
> > >> Thanks for the explanations, Josh. This sounds very doable. Few more
> > >> comments inline below.
> > >>
> > >> James
> > >>
> > >>
> > >> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com>
> > wrote:
> > >>
> > >>
> > >>>
> > >>> On 4/30/14, 3:33 AM, James Taylor wrote:
> > >>>
> > >>>  On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
> > >>>> wrote:
> > >>>>
> > >>>>   @Josh - it's less baked in than you'd think on the client where
> the
> > >>>> query
> > >>>>
> > >>>>>
> > >>>>>  parsing, compilation, optimization, and orchestration occurs. The
> > >>>>>> client/server interaction is hidden behind the
> > ConnectionQueryServices
> > >>>>>> interface, the scanning behind ResultIterator (in
> > >>>>>> particular ScanningResultIterator), the DML behind MutationState,
> > and
> > >>>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
> > >>>>>> require
> > >>>>>> some more abstraction, but probably not too bad, though. On the
> > >>>>>> server-side, the entry points would all be different and that's
> > where
> > >>>>>> I'd
> > >>>>>> need your insights for what's possible.
> > >>>>>>
> > >>>>>>
> > >>>>>>  Definitely. I'm a little concerned about what's expected to be
> > >>>>> provided
> > >>>>> by
> > >>>>> the "database" (HBase, Accumulo) as I believe HBase is a little
> more
> > >>>>> flexible in allowing writes internally where Accumulo has thus far
> > said
> > >>>>> "you're gonna have a bad time".
> > >>>>>
> > >>>>>
> > >>>>
> > >>>> Tell me more about what you mean by "allowing writes internally".
> > >>>>
> > >>>>
> > >>> Haha, sorry, that was a sufficiently ominous statement with
> > insufficient
> > >>> context.
> > >>>
> > >>> For discussion sake, let's just say HBase coprocessors and Accumulo
> > >>> iterators are equivalent, purely in the scope of "running server-side
> > >>> code"
> > >>> (in the RegionServer/TabletServer). However, there is a notable
> > >>> difference
> > >>> in the pipeline where each of those are implemented.
> > >>>
> > >>> Coprocessors have built-in hooks that let you get updates on
> > >>> PUT/GET/DELETE/etc as well as pre and post each of those operations.
> In
> > >>> other words, they provide hooks at a "high database level".
> > >>>
> > >>> Iterators tend to be much closer to the data itself, only dealing
> with
> > >>> streams of data (other iterators stacked on one another). Iterators
> > >>> implement versioning, visibilities, and can even implement complex
> > >>> searches. The downside of this approach is that iterators lack any
> > means
> > >>> to
> > >>> safely write data _outside of the sorted Key-Value pairs in the
> tablet
> > >>> currently being processed_. It's possible to make in tablet updates,
> > but
> > >>> sorted order within a large tablet might make this difficult as well.
> > >>>
> > >>> This is why I was thinking percolator would be a better solution, as
> > it's
> > >>> meant for handling updates like this server-side. However, I imagine
> it
> > >>> would be possible, in the short-term, to make some separate process
> > >>> between
> > >>> Phoenix and Accumulo which handles writes.
> > >>>
> > >>
> > >>
> > >> Another fallback might be to do global index maintenance on the
> client.
> > >> It'd just be more expensive, especially if you want to handle
> > out-of-order
> > >> updates (which are particularly tricky, as you have to get multiple
> > >> versions of the rows to work out all the different scenarios here).
> > >>
> > >> A second fallback might be to support only local indexing. Does
> Accumulo
> > >> have the concept of a "custom load balancer" that would allow you to
> > >> co-locate two regions from different tables? The local-index features
> > has
> > >> kind of driven some feature requests on that front for HBase - mainly
> > >> callbacks when a region is split or re-located. The rows of the local
> > >> index
> > >> are prefixed with the region start key to keep them together and
> > identify
> > >> them.
> > >>
> > >
> > > Agreed with what Bill said. Co-locating indices within the same row
> > > simplifies this a bit, IMO.
> > >
> > >
> > > <snip/>
> > >
> > >
> > >
> > >>>>>
> > >>>>
> > >>>> There's not a lot of hard/fast requirements. Most of what Phoenix
> does
> > >>>> is
> > >>>> to optimize performance by leveraging the capabilities of the
> server.
> > In
> > >>>> terms of hard/fast requirements, these come to mind:
> > >>>> - data is returned in row key order from range scans
> > >>>> - a scan may set a start key/stop key to do a range scan
> > >>>> - a row key may be composed of arbitrary bytes
> > >>>> - a client may "pre-split" a table by providing the region
> boundaries
> > at
> > >>>> table create time (we rely on this for salting to prevent
> hotspotting:
> > >>>> http://phoenix.incubator.apache.org/salted.html).
> > >>>> - the client has access to the region boundaries of a table (this
> > allows
> > >>>> for better parallelization)
> > >>>> - the client may issue chunk up a scan into smaller, multiple scans
> > and
> > >>>> run
> > >>>> them in parallel
> > >>>> Some of these may be a bit squishy, as there may be existing
> machinery
> > >>>> already in your client programming model that could be leverage. The
> > >>>> client
> > >>>> API of HBase, for example, does not provide the ability out of the
> box
> > >>>> to
> > >>>> parallelize a scan, so this is something Phoenix had to add on top
> > >>>> (through
> > >>>> chunking up scans at or within region boundaries).
> > >>>>
> > >>>>
> > >>> All of these look fine. The Accumulo BatchScanner does that
> > >>> parallelization for you which is really nice (handling tablet
> migration
> > >>> and
> > >>> all that fun stuff transparently).
> > >>>
> > >>
> > >>
> > >> That's nice that Accumulo has this built-in. Does it allow the client
> to
> > >> specify the split points for the scan in some way?
> > >>
> > >
> > > Assuming I understand properly, you don't need to be cognizant of the
> > > splits. You just specify the Ranges (where each Range is a start key
> and
> > > end key) and the Accumulo client API does the rest. You can be
> efficient
> > by
> > > structuring your data so that you don't touch every tabletserver for
> > every
> > > query -- this seems to be what's being suggested.
> > >
> > > <snip/>
> > >
> > > What do you think is next, James?
> > >
> > > I know I won't have a lot of time to devote into heavy development with
> > > what I've already signed up for in the next few months, but I'd still
> > like
> > > to try to help out where possible. Is anyone else on the Accumulo side
> > > interested in getting involved?
> > >
> >
>

Re: SQL layer over Accumulo?

[William Slacum <wi...@accumulo.net>]

So there may be a bit of confusion with storing index and data in the same
row. By "row" I just mean the logical Accumulo unit, not a "row" as in
"thing in my relational table." Synonyms for "row" in this scheme are
"shard" and "document partition".

You can store multiple documents and indices for those documents in
different column families within the same row. You then have separate
readers for the indices and document data ("sources" in Iterator terms).
Point and range queries are still possible in this fashion, and are made
even easier if there's another level that maps terms to
rows/shards/partition. The wikisearch example is an (admittedly rough)
implementation of this.

I think looking at how "buddy" regions work may help clarify things, since
I imagine it works similarly. If the coprocessor is just reading from a
region "I", that that contains index data for only region "D", then that
maps pretty well to an iterator scanning index data from a column family
"I" and fetching documents from a column family "D".



On Thu, May 8, 2014 at 1:09 AM, James Taylor <ja...@apache.org> wrote:

> Sorry for the delay in getting back to you - things got a bit crazy with
> our graduation and HBaseCon happening at the same time.
>
> @Josh & Bill - r.e. Co-locating indices within the same row simplifies this
> a bit.
> The secondary indexes need to be in row key order by the indexed columns,
> so co-locating them in the data table wouldn't allow the lookup and range
> scan abilities we'd need. The advantage of the index is that you don't need
> to look at all the data, but can do a point lookup or range scan based on
> the usage of the indexed columns in a query.
>
> @Josh - r.e. Assuming I understand properly, you don't need to be cognizant
> of the splits. You just specify the Ranges (where each Range is a start key
> and end key) and the Accumulo client API does the rest.
>
> Typically the Ranges are merge sorted on the client, so this might require
> an extension to the Accumulo client.
>
> r.e. Next steps.
>
> We'd definitely need an expert on the Accumulo side to proceed. I'm happy
> to help on the Phoenix side - I'll post a note on our dev list too to see
> if there are other folks interested as well. Given the similarities between
> Accumulo and HBase and the abstraction Phoenix already has in place, I
> don't think the effort would be large to get something up and running.
> Maybe a phased approach, would make sense: first with query support and
> next with secondary index support?
>
> Not sure where this stacks up in terms of priority for you all. At
> Salesforce, we saw a specific need for this with HBase, the "big data
> store" on top of which we'd choose to standardize. We realized early on
> that we'd never get the adoption we wanted without providing a different,
> more familiar programming model: namely SQL. Since we were targeting
> supporting interactive web-based applications, anything map/reduce based
> wasn't a fit which led us to create Phoenix. Perhaps there are members in
> your community in the same boat?
>
> Thanks,
> James
>
>
>
> On Fri, May 2, 2014 at 1:44 PM, Josh Elser <jo...@gmail.com> wrote:
>
> > On 5/1/14, 2:24 AM, James Taylor wrote:
> >
> >> Thanks for the explanations, Josh. This sounds very doable. Few more
> >> comments inline below.
> >>
> >> James
> >>
> >>
> >> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com>
> wrote:
> >>
> >>
> >>>
> >>> On 4/30/14, 3:33 AM, James Taylor wrote:
> >>>
> >>>  On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
> >>>> wrote:
> >>>>
> >>>>   @Josh - it's less baked in than you'd think on the client where the
> >>>> query
> >>>>
> >>>>>
> >>>>>  parsing, compilation, optimization, and orchestration occurs. The
> >>>>>> client/server interaction is hidden behind the
> ConnectionQueryServices
> >>>>>> interface, the scanning behind ResultIterator (in
> >>>>>> particular ScanningResultIterator), the DML behind MutationState,
> and
> >>>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
> >>>>>> require
> >>>>>> some more abstraction, but probably not too bad, though. On the
> >>>>>> server-side, the entry points would all be different and that's
> where
> >>>>>> I'd
> >>>>>> need your insights for what's possible.
> >>>>>>
> >>>>>>
> >>>>>>  Definitely. I'm a little concerned about what's expected to be
> >>>>> provided
> >>>>> by
> >>>>> the "database" (HBase, Accumulo) as I believe HBase is a little more
> >>>>> flexible in allowing writes internally where Accumulo has thus far
> said
> >>>>> "you're gonna have a bad time".
> >>>>>
> >>>>>
> >>>>
> >>>> Tell me more about what you mean by "allowing writes internally".
> >>>>
> >>>>
> >>> Haha, sorry, that was a sufficiently ominous statement with
> insufficient
> >>> context.
> >>>
> >>> For discussion sake, let's just say HBase coprocessors and Accumulo
> >>> iterators are equivalent, purely in the scope of "running server-side
> >>> code"
> >>> (in the RegionServer/TabletServer). However, there is a notable
> >>> difference
> >>> in the pipeline where each of those are implemented.
> >>>
> >>> Coprocessors have built-in hooks that let you get updates on
> >>> PUT/GET/DELETE/etc as well as pre and post each of those operations. In
> >>> other words, they provide hooks at a "high database level".
> >>>
> >>> Iterators tend to be much closer to the data itself, only dealing with
> >>> streams of data (other iterators stacked on one another). Iterators
> >>> implement versioning, visibilities, and can even implement complex
> >>> searches. The downside of this approach is that iterators lack any
> means
> >>> to
> >>> safely write data _outside of the sorted Key-Value pairs in the tablet
> >>> currently being processed_. It's possible to make in tablet updates,
> but
> >>> sorted order within a large tablet might make this difficult as well.
> >>>
> >>> This is why I was thinking percolator would be a better solution, as
> it's
> >>> meant for handling updates like this server-side. However, I imagine it
> >>> would be possible, in the short-term, to make some separate process
> >>> between
> >>> Phoenix and Accumulo which handles writes.
> >>>
> >>
> >>
> >> Another fallback might be to do global index maintenance on the client.
> >> It'd just be more expensive, especially if you want to handle
> out-of-order
> >> updates (which are particularly tricky, as you have to get multiple
> >> versions of the rows to work out all the different scenarios here).
> >>
> >> A second fallback might be to support only local indexing. Does Accumulo
> >> have the concept of a "custom load balancer" that would allow you to
> >> co-locate two regions from different tables? The local-index features
> has
> >> kind of driven some feature requests on that front for HBase - mainly
> >> callbacks when a region is split or re-located. The rows of the local
> >> index
> >> are prefixed with the region start key to keep them together and
> identify
> >> them.
> >>
> >
> > Agreed with what Bill said. Co-locating indices within the same row
> > simplifies this a bit, IMO.
> >
> >
> > <snip/>
> >
> >
> >
> >>>>>
> >>>>
> >>>> There's not a lot of hard/fast requirements. Most of what Phoenix does
> >>>> is
> >>>> to optimize performance by leveraging the capabilities of the server.
> In
> >>>> terms of hard/fast requirements, these come to mind:
> >>>> - data is returned in row key order from range scans
> >>>> - a scan may set a start key/stop key to do a range scan
> >>>> - a row key may be composed of arbitrary bytes
> >>>> - a client may "pre-split" a table by providing the region boundaries
> at
> >>>> table create time (we rely on this for salting to prevent hotspotting:
> >>>> http://phoenix.incubator.apache.org/salted.html).
> >>>> - the client has access to the region boundaries of a table (this
> allows
> >>>> for better parallelization)
> >>>> - the client may issue chunk up a scan into smaller, multiple scans
> and
> >>>> run
> >>>> them in parallel
> >>>> Some of these may be a bit squishy, as there may be existing machinery
> >>>> already in your client programming model that could be leverage. The
> >>>> client
> >>>> API of HBase, for example, does not provide the ability out of the box
> >>>> to
> >>>> parallelize a scan, so this is something Phoenix had to add on top
> >>>> (through
> >>>> chunking up scans at or within region boundaries).
> >>>>
> >>>>
> >>> All of these look fine. The Accumulo BatchScanner does that
> >>> parallelization for you which is really nice (handling tablet migration
> >>> and
> >>> all that fun stuff transparently).
> >>>
> >>
> >>
> >> That's nice that Accumulo has this built-in. Does it allow the client to
> >> specify the split points for the scan in some way?
> >>
> >
> > Assuming I understand properly, you don't need to be cognizant of the
> > splits. You just specify the Ranges (where each Range is a start key and
> > end key) and the Accumulo client API does the rest. You can be efficient
> by
> > structuring your data so that you don't touch every tabletserver for
> every
> > query -- this seems to be what's being suggested.
> >
> > <snip/>
> >
> > What do you think is next, James?
> >
> > I know I won't have a lot of time to devote into heavy development with
> > what I've already signed up for in the next few months, but I'd still
> like
> > to try to help out where possible. Is anyone else on the Accumulo side
> > interested in getting involved?
> >
>

Re: SQL layer over Accumulo?

[James Taylor <ja...@apache.org>]

Sorry for the delay in getting back to you - things got a bit crazy with
our graduation and HBaseCon happening at the same time.

@Josh & Bill - r.e. Co-locating indices within the same row simplifies this
a bit.
The secondary indexes need to be in row key order by the indexed columns,
so co-locating them in the data table wouldn't allow the lookup and range
scan abilities we'd need. The advantage of the index is that you don't need
to look at all the data, but can do a point lookup or range scan based on
the usage of the indexed columns in a query.

@Josh - r.e. Assuming I understand properly, you don't need to be cognizant
of the splits. You just specify the Ranges (where each Range is a start key
and end key) and the Accumulo client API does the rest.

Typically the Ranges are merge sorted on the client, so this might require
an extension to the Accumulo client.

r.e. Next steps.

We'd definitely need an expert on the Accumulo side to proceed. I'm happy
to help on the Phoenix side - I'll post a note on our dev list too to see
if there are other folks interested as well. Given the similarities between
Accumulo and HBase and the abstraction Phoenix already has in place, I
don't think the effort would be large to get something up and running.
Maybe a phased approach, would make sense: first with query support and
next with secondary index support?

Not sure where this stacks up in terms of priority for you all. At
Salesforce, we saw a specific need for this with HBase, the "big data
store" on top of which we'd choose to standardize. We realized early on
that we'd never get the adoption we wanted without providing a different,
more familiar programming model: namely SQL. Since we were targeting
supporting interactive web-based applications, anything map/reduce based
wasn't a fit which led us to create Phoenix. Perhaps there are members in
your community in the same boat?

Thanks,
James



On Fri, May 2, 2014 at 1:44 PM, Josh Elser <jo...@gmail.com> wrote:

> On 5/1/14, 2:24 AM, James Taylor wrote:
>
>> Thanks for the explanations, Josh. This sounds very doable. Few more
>> comments inline below.
>>
>> James
>>
>>
>> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com> wrote:
>>
>>
>>>
>>> On 4/30/14, 3:33 AM, James Taylor wrote:
>>>
>>>  On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
>>>> wrote:
>>>>
>>>>   @Josh - it's less baked in than you'd think on the client where the
>>>> query
>>>>
>>>>>
>>>>>  parsing, compilation, optimization, and orchestration occurs. The
>>>>>> client/server interaction is hidden behind the ConnectionQueryServices
>>>>>> interface, the scanning behind ResultIterator (in
>>>>>> particular ScanningResultIterator), the DML behind MutationState, and
>>>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
>>>>>> require
>>>>>> some more abstraction, but probably not too bad, though. On the
>>>>>> server-side, the entry points would all be different and that's where
>>>>>> I'd
>>>>>> need your insights for what's possible.
>>>>>>
>>>>>>
>>>>>>  Definitely. I'm a little concerned about what's expected to be
>>>>> provided
>>>>> by
>>>>> the "database" (HBase, Accumulo) as I believe HBase is a little more
>>>>> flexible in allowing writes internally where Accumulo has thus far said
>>>>> "you're gonna have a bad time".
>>>>>
>>>>>
>>>>
>>>> Tell me more about what you mean by "allowing writes internally".
>>>>
>>>>
>>> Haha, sorry, that was a sufficiently ominous statement with insufficient
>>> context.
>>>
>>> For discussion sake, let's just say HBase coprocessors and Accumulo
>>> iterators are equivalent, purely in the scope of "running server-side
>>> code"
>>> (in the RegionServer/TabletServer). However, there is a notable
>>> difference
>>> in the pipeline where each of those are implemented.
>>>
>>> Coprocessors have built-in hooks that let you get updates on
>>> PUT/GET/DELETE/etc as well as pre and post each of those operations. In
>>> other words, they provide hooks at a "high database level".
>>>
>>> Iterators tend to be much closer to the data itself, only dealing with
>>> streams of data (other iterators stacked on one another). Iterators
>>> implement versioning, visibilities, and can even implement complex
>>> searches. The downside of this approach is that iterators lack any means
>>> to
>>> safely write data _outside of the sorted Key-Value pairs in the tablet
>>> currently being processed_. It's possible to make in tablet updates, but
>>> sorted order within a large tablet might make this difficult as well.
>>>
>>> This is why I was thinking percolator would be a better solution, as it's
>>> meant for handling updates like this server-side. However, I imagine it
>>> would be possible, in the short-term, to make some separate process
>>> between
>>> Phoenix and Accumulo which handles writes.
>>>
>>
>>
>> Another fallback might be to do global index maintenance on the client.
>> It'd just be more expensive, especially if you want to handle out-of-order
>> updates (which are particularly tricky, as you have to get multiple
>> versions of the rows to work out all the different scenarios here).
>>
>> A second fallback might be to support only local indexing. Does Accumulo
>> have the concept of a "custom load balancer" that would allow you to
>> co-locate two regions from different tables? The local-index features has
>> kind of driven some feature requests on that front for HBase - mainly
>> callbacks when a region is split or re-located. The rows of the local
>> index
>> are prefixed with the region start key to keep them together and identify
>> them.
>>
>
> Agreed with what Bill said. Co-locating indices within the same row
> simplifies this a bit, IMO.
>
>
> <snip/>
>
>
>
>>>>>
>>>>
>>>> There's not a lot of hard/fast requirements. Most of what Phoenix does
>>>> is
>>>> to optimize performance by leveraging the capabilities of the server. In
>>>> terms of hard/fast requirements, these come to mind:
>>>> - data is returned in row key order from range scans
>>>> - a scan may set a start key/stop key to do a range scan
>>>> - a row key may be composed of arbitrary bytes
>>>> - a client may "pre-split" a table by providing the region boundaries at
>>>> table create time (we rely on this for salting to prevent hotspotting:
>>>> http://phoenix.incubator.apache.org/salted.html).
>>>> - the client has access to the region boundaries of a table (this allows
>>>> for better parallelization)
>>>> - the client may issue chunk up a scan into smaller, multiple scans and
>>>> run
>>>> them in parallel
>>>> Some of these may be a bit squishy, as there may be existing machinery
>>>> already in your client programming model that could be leverage. The
>>>> client
>>>> API of HBase, for example, does not provide the ability out of the box
>>>> to
>>>> parallelize a scan, so this is something Phoenix had to add on top
>>>> (through
>>>> chunking up scans at or within region boundaries).
>>>>
>>>>
>>> All of these look fine. The Accumulo BatchScanner does that
>>> parallelization for you which is really nice (handling tablet migration
>>> and
>>> all that fun stuff transparently).
>>>
>>
>>
>> That's nice that Accumulo has this built-in. Does it allow the client to
>> specify the split points for the scan in some way?
>>
>
> Assuming I understand properly, you don't need to be cognizant of the
> splits. You just specify the Ranges (where each Range is a start key and
> end key) and the Accumulo client API does the rest. You can be efficient by
> structuring your data so that you don't touch every tabletserver for every
> query -- this seems to be what's being suggested.
>
> <snip/>
>
> What do you think is next, James?
>
> I know I won't have a lot of time to devote into heavy development with
> what I've already signed up for in the next few months, but I'd still like
> to try to help out where possible. Is anyone else on the Accumulo side
> interested in getting involved?
>

Re: SQL layer over Accumulo?

[Josh Elser <jo...@gmail.com>]

On 5/1/14, 2:24 AM, James Taylor wrote:
> Thanks for the explanations, Josh. This sounds very doable. Few more
> comments inline below.
>
> James
>
>
> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com> wrote:
>
>>
>>
>> On 4/30/14, 3:33 AM, James Taylor wrote:
>>
>>> On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
>>> wrote:
>>>
>>>   @Josh - it's less baked in than you'd think on the client where the query
>>>>
>>>>> parsing, compilation, optimization, and orchestration occurs. The
>>>>> client/server interaction is hidden behind the ConnectionQueryServices
>>>>> interface, the scanning behind ResultIterator (in
>>>>> particular ScanningResultIterator), the DML behind MutationState, and
>>>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
>>>>> require
>>>>> some more abstraction, but probably not too bad, though. On the
>>>>> server-side, the entry points would all be different and that's where
>>>>> I'd
>>>>> need your insights for what's possible.
>>>>>
>>>>>
>>>> Definitely. I'm a little concerned about what's expected to be provided
>>>> by
>>>> the "database" (HBase, Accumulo) as I believe HBase is a little more
>>>> flexible in allowing writes internally where Accumulo has thus far said
>>>> "you're gonna have a bad time".
>>>>
>>>
>>>
>>> Tell me more about what you mean by "allowing writes internally".
>>>
>>
>> Haha, sorry, that was a sufficiently ominous statement with insufficient
>> context.
>>
>> For discussion sake, let's just say HBase coprocessors and Accumulo
>> iterators are equivalent, purely in the scope of "running server-side code"
>> (in the RegionServer/TabletServer). However, there is a notable difference
>> in the pipeline where each of those are implemented.
>>
>> Coprocessors have built-in hooks that let you get updates on
>> PUT/GET/DELETE/etc as well as pre and post each of those operations. In
>> other words, they provide hooks at a "high database level".
>>
>> Iterators tend to be much closer to the data itself, only dealing with
>> streams of data (other iterators stacked on one another). Iterators
>> implement versioning, visibilities, and can even implement complex
>> searches. The downside of this approach is that iterators lack any means to
>> safely write data _outside of the sorted Key-Value pairs in the tablet
>> currently being processed_. It's possible to make in tablet updates, but
>> sorted order within a large tablet might make this difficult as well.
>>
>> This is why I was thinking percolator would be a better solution, as it's
>> meant for handling updates like this server-side. However, I imagine it
>> would be possible, in the short-term, to make some separate process between
>> Phoenix and Accumulo which handles writes.
>
>
> Another fallback might be to do global index maintenance on the client.
> It'd just be more expensive, especially if you want to handle out-of-order
> updates (which are particularly tricky, as you have to get multiple
> versions of the rows to work out all the different scenarios here).
>
> A second fallback might be to support only local indexing. Does Accumulo
> have the concept of a "custom load balancer" that would allow you to
> co-locate two regions from different tables? The local-index features has
> kind of driven some feature requests on that front for HBase - mainly
> callbacks when a region is split or re-located. The rows of the local index
> are prefixed with the region start key to keep them together and identify
> them.

Agreed with what Bill said. Co-locating indices within the same row 
simplifies this a bit, IMO.


<snip/>

>>>>
>>>
>>>
>>> There's not a lot of hard/fast requirements. Most of what Phoenix does is
>>> to optimize performance by leveraging the capabilities of the server. In
>>> terms of hard/fast requirements, these come to mind:
>>> - data is returned in row key order from range scans
>>> - a scan may set a start key/stop key to do a range scan
>>> - a row key may be composed of arbitrary bytes
>>> - a client may "pre-split" a table by providing the region boundaries at
>>> table create time (we rely on this for salting to prevent hotspotting:
>>> http://phoenix.incubator.apache.org/salted.html).
>>> - the client has access to the region boundaries of a table (this allows
>>> for better parallelization)
>>> - the client may issue chunk up a scan into smaller, multiple scans and
>>> run
>>> them in parallel
>>> Some of these may be a bit squishy, as there may be existing machinery
>>> already in your client programming model that could be leverage. The
>>> client
>>> API of HBase, for example, does not provide the ability out of the box to
>>> parallelize a scan, so this is something Phoenix had to add on top
>>> (through
>>> chunking up scans at or within region boundaries).
>>>
>>
>> All of these look fine. The Accumulo BatchScanner does that
>> parallelization for you which is really nice (handling tablet migration and
>> all that fun stuff transparently).
>
>
> That's nice that Accumulo has this built-in. Does it allow the client to
> specify the split points for the scan in some way?

Assuming I understand properly, you don't need to be cognizant of the 
splits. You just specify the Ranges (where each Range is a start key and 
end key) and the Accumulo client API does the rest. You can be efficient 
by structuring your data so that you don't touch every tabletserver for 
every query -- this seems to be what's being suggested.

<snip/>

What do you think is next, James?

I know I won't have a lot of time to devote into heavy development with 
what I've already signed up for in the next few months, but I'd still 
like to try to help out where possible. Is anyone else on the Accumulo 
side interested in getting involved?

Re: SQL layer over Accumulo?

[William Slacum <wi...@accumulo.net>]

The wikisearch example provides something similar to a local index. Rather
than stuff things into two tablets, a single row in accumulo contains both
the index and data stored in separate column families. Iterator trees are
used to execute queries and retrieve data with that row.


On Thu, May 1, 2014 at 2:24 AM, James Taylor <ja...@apache.org> wrote:

> Thanks for the explanations, Josh. This sounds very doable. Few more
> comments inline below.
>
> James
>
>
> On Wed, Apr 30, 2014 at 8:37 AM, Josh Elser <jo...@gmail.com> wrote:
>
> >
> >
> > On 4/30/14, 3:33 AM, James Taylor wrote:
> >
> >> On Tue, Apr 29, 2014 at 11:57 AM, Josh Elser <jo...@gmail.com>
> >> wrote:
> >>
> >>  @Josh - it's less baked in than you'd think on the client where the
> query
> >>>
> >>>> parsing, compilation, optimization, and orchestration occurs. The
> >>>> client/server interaction is hidden behind the ConnectionQueryServices
> >>>> interface, the scanning behind ResultIterator (in
> >>>> particular ScanningResultIterator), the DML behind MutationState, and
> >>>> KeyValue interaction behind KeyValueBuilder. Yes, though, it would
> >>>> require
> >>>> some more abstraction, but probably not too bad, though. On the
> >>>> server-side, the entry points would all be different and that's where
> >>>> I'd
> >>>> need your insights for what's possible.
> >>>>
> >>>>
> >>> Definitely. I'm a little concerned about what's expected to be provided
> >>> by
> >>> the "database" (HBase, Accumulo) as I believe HBase is a little more
> >>> flexible in allowing writes internally where Accumulo has thus far said
> >>> "you're gonna have a bad time".
> >>>
> >>
> >>
> >> Tell me more about what you mean by "allowing writes internally".
> >>
> >
> > Haha, sorry, that was a sufficiently ominous statement with insufficient
> > context.
> >
> > For discussion sake, let's just say HBase coprocessors and Accumulo
> > iterators are equivalent, purely in the scope of "running server-side
> code"
> > (in the RegionServer/TabletServer). However, there is a notable
> difference
> > in the pipeline where each of those are implemented.
> >
> > Coprocessors have built-in hooks that let you get updates on
> > PUT/GET/DELETE/etc as well as pre and post each of those operations. In
> > other words, they provide hooks at a "high database level".
> >
> > Iterators tend to be much closer to the data itself, only dealing with
> > streams of data (other iterators stacked on one another). Iterators
> > implement versioning, visibilities, and can even implement complex
> > searches. The downside of this approach is that iterators lack any means
> to
> > safely write data _outside of the sorted Key-Value pairs in the tablet
> > currently being processed_. It's possible to make in tablet updates, but
> > sorted order within a large tablet might make this difficult as well.
> >
> > This is why I was thinking percolator would be a better solution, as it's
> > meant for handling updates like this server-side. However, I imagine it
> > would be possible, in the short-term, to make some separate process
> between
> > Phoenix and Accumulo which handles writes.
>
>
> Another fallback might be to do global index maintenance on the client.
> It'd just be more expensive, especially if you want to handle out-of-order
> updates (which are particularly tricky, as you have to get multiple
> versions of the rows to work out all the different scenarios here).
>
> A second fallback might be to support only local indexing. Does Accumulo
> have the concept of a "custom load balancer" that would allow you to
> co-locate two regions from different tables? The local-index features has
> kind of driven some feature requests on that front for HBase - mainly
> callbacks when a region is split or re-located. The rows of the local index
> are prefixed with the region start key to keep them together and identify
> them.
>
> >
> >
> >
> >>
> >>>
> >>>   @Eric - I agree about having txn support (probably through snapshot
> >>>
> >>>> isolation) by controlling the timestamp, and then layering indexing on
> >>>> top
> >>>> of that. That's where we're headed. But I wouldn't let that stop the
> >>>> effort
> >>>> - it would just be layered on top of what's already there. FWIW,
> there's
> >>>> another interesting indexing model that has been termed "local
> >>>> indexing"(
> >>>> https://github.com/Huawei-Hadoop/hindex) which is being worked on
> right
> >>>> now
> >>>> (should be available in either our 4.1 or 4.2 release). In this model,
> >>>> the
> >>>> table data and index data are co-located on the same region server
> >>>> through
> >>>> a kind of "buddy" region mechanism. The advantage is that you take no
> >>>> hit
> >>>> at write time, as you're writing both the index and table data
> together.
> >>>> Not sure how/if this would transfer over to the Accumulo world.
> >>>>
> >>>>
> >>> Interesting. Given that Accumulo doesn't have a fixed column family
> >>> schema, this might make index generation even easier (maybe "cleaner"
> is
> >>> the proper word). You could easily co-locate the indices with the data,
> >>> given them a proper name.
> >>>
> >>>
> >> With HBase, you can do something similar (though, you're right, you'd
> need
> >> to create the column family upfront or take the hit of creating it
> >> dynamically - that's a nice feature that Accumulo has). The reason this
> >> doesn't work is that you need a different row key so that the index rows
> >> are ordered according to their indexed column values. If you put it in a
> >> column family of the data table, they're ordered in the same way as the
> >> data table. This makes range scans over index tables very expensive, as
> >> the
> >> rows would need to be re-ordered.
> >>
> >>
> > Ah, of course. You need the term up front to make it sort properly.
> >
> >
> >
> >>> Problem still exists that we don't have a solid way to do this solely
> >>> inside of Accumulo ATM. I'd imagine that if someone stepped up to
> >>> implement
> >>> coprocessors, we'd be taking the route of a separate, standalone
> process
> >>> (as opposed to in-RegionServer). Hypothetically, we could do the same
> for
> >>> Phoenix in the short-term.
> >>>
> >>> Can you quantify what would be expected by Accumulo to integrate with
> >>> Phoenix (maybe list what exactly is done inside of HBase at a high
> >>> level?)
> >>> so that we could give some more targeted ideas/feelings as to what the
> >>> level of work would be inside Accumulo?
> >>>
> >>
> >>
> >> There's not a lot of hard/fast requirements. Most of what Phoenix does
> is
> >> to optimize performance by leveraging the capabilities of the server. In
> >> terms of hard/fast requirements, these come to mind:
> >> - data is returned in row key order from range scans
> >> - a scan may set a start key/stop key to do a range scan
> >> - a row key may be composed of arbitrary bytes
> >> - a client may "pre-split" a table by providing the region boundaries at
> >> table create time (we rely on this for salting to prevent hotspotting:
> >> http://phoenix.incubator.apache.org/salted.html).
> >> - the client has access to the region boundaries of a table (this allows
> >> for better parallelization)
> >> - the client may issue chunk up a scan into smaller, multiple scans and
> >> run
> >> them in parallel
> >> Some of these may be a bit squishy, as there may be existing machinery
> >> already in your client programming model that could be leverage. The
> >> client
> >> API of HBase, for example, does not provide the ability out of the box
> to
> >> parallelize a scan, so this is something Phoenix had to add on top
> >> (through
> >> chunking up scans at or within region boundaries).
> >>
> >
> > All of these look fine. The Accumulo BatchScanner does that
> > parallelization for you which is really nice (handling tablet migration
> and
> > all that fun stuff transparently).
>
>
> That's nice that Accumulo has this built-in. Does it allow the client to
> specify the split points for the scan in some way?
>
> >
> >
> >
> >  Phoenix manages the metadata of your tables (tables, columns, indexes,
> >> views, etc) in an HBase table. DDL statements such as CREATE TABLE, DROP
> >> TABLE, ALTER TABLE are atomic, transactional operations b/c we don't
> want
> >> our metadata table to get in a corrupt state. To accomplish this, we
> rely
> >> on:
> >> - setting a "split policy" that ensures that the table data for a given
> >> "tenant" (we support multi-tenancy:
> >> http://phoenix.incubator.apache.org/multi-tenancy.html) stay together
> in
> >> the same region.
> >> - putting the data using an API that guarantees that either the entire
> >> batch of mutations succeed or fail completely.
> >> Again, these are details of our implementation on HBase which do not
> >> necessarily need to be implemented in the same way on a different
> system.
> >>
> >
> > I'd have to look again at how our mutation failures are handled (or
> > someone else can chime in). This might be something to keep an eye on
> > depending on the distribution of mutations in regards to tables.
> >
> >
> >  Phoenix supports sequences which are atomically incremented values. This
> >> is
> >> done through a coprocessor currently, due to some limitations with the
> >> HBase Increment API, but the idea is the same as an atomic increment.
> >>
> >
> > Conditional Mutations in the about-to-be-released version 1.6.0 will
> > provide this.
> >
> >
> >  Phoenix does the following push down:
> >> - the WHERE clause gets transformed into three things: a start/stop key
> of
> >> a scan, a skip scan filter to efficiently navigate the key space (see
> >> http://phoenix-hbase.blogspot.com/2013/05/demystifying-skip-
> >> scan-in-phoenix.html),
> >> and a custom filter to rule out a row based on some java code that does
> >> expression evaluation.
> >> - the GROUP BY clause gets pushed to the server and a coprocessor runs
> the
> >> scan on each region so that the client doesn't have to get back all the
> >> raw
> >> data. Instead, the client gets back the aggregated data (to conserve
> >> network bandwidth and to run the scan where the data lives). The client
> >> then does a final merge sort.
> >>
> >
> > I've written an iterator to do a group by previously. Depending on the
> > schema this is fine.
> >
> >
> >  - the ORDER BY clause used in combination with the LIMIT clause is a
> TopN
> >> query. We optimize this by each region holding on to the top N values
> with
> >> the client then doing a merge sort with the limit applied.
> >>
> >
> > This is an interesting one. If you remove the possibility of tablets
> > splitting out from underneath you and you had a view of the splits, you
> > could probably pull it off.
> >
> >
> >  - the ORDER BY clause on it's own gets executed on each region (spooled
> >> using memory mapped files) and then the client does a merge sort. This
> >> spooling could potentially be done on the client side.
> >>
> >
> > Unless we can do some trickery with the schema, yeah, client side.
> >
> >
> >  - joins are executed as a broadcast hash join. We run one side of the
> >> query
> >> (with the filters applied), compact the results, and send them to each
> >> region server where they are cached while we run the other side of the
> >> query. A coprocessor then does a map lookup (equi-joins only are
> supported
> >> currently) to join based on the join key and returns the joined results
> >> (i.e. the concatenated values in a single, condensed key value as access
> >> from the client is positional post-join).
> >>
> >
> > The join approach would need to be implemented some other way for the
> > earlier stated comparison of iterators and coprocessors.
>
>
> Client-side could be another fallback. The coprocessor approach is really
> only a big win in two cases: if you have a join which doesn't have many
> matches (as those rows get filtered on the server-side), or for correlated
> sub queries or exists queries where you can filter or collapse many rows to
> one or none on the server-side rather than return them all to the client.
>
> >
> >
> >  For our global secondary indexes (local secondary indexes are different
> as
> >> we discussed already), we trap updates to the data table through a
> >> coprocessor. For index maintenance you need to know when a change occurs
> >> to
> >> a data row what the prior value of the row was. The reason is because
> you
> >> need to delete the index row corresponding to the old data row and then
> >> insert the index row corresponding to the new value (remember, the index
> >> value makes up the row key). By doing this operation through a
> >> coprocessor,
> >> we know that we can get the prior data row state locally. We still need
> to
> >> issue a Put from one region server to another, but this isn't really an
> >> extra hop, as if it was done on the client, the same hop would need to
> be
> >> done (but the old row state would need to be pulled over to the client
> >> which is not necessary with the coprocessor based approach). For more on
> >> global secondary indexing, see
> >> http://phoenix.incubator.apache.org/secondary_indexing.html (there are
> >> some
> >> good presentations at the end of the page that provide more technical
> >> detail).
> >>
> >
> > Right, you want to remove the old index value and update a new index
> value
> > (actually being two unique keys) in the same transaction to ensure a
> valid
> > index. Or, at least ensure that you never remove the old value, and die
> > before inserting the new value.
> >
> > Again, not going to work well in an iterator.
> >
> >
> >  Phoenix also allows "point-in-time" queries where a client may
> establish a
> >> connection at an earlier timestamp. If your table is setup to keep
> >> multiple
> >> versions of the same row, then you can query "back-in-time" and will see
> >> the data as it was at that point. We more or less get this for free with
> >> the MVCC model of HBase by specifying a max timestamp on a scan. One
> >> slightly tricky bit is we correlate the current DDL of your table based
> on
> >> the same timestamp as with your data. So when you go back-in-time like
> >> this, you'll also see the structure of your table as it was at time
> also.
> >>
> >
> > I don't see this as a problem. As long as we remove the versioning
> > iterator from a table (which keeps the most recent version of a key by
> > default), it should be pretty easy to implement an iterator which adheres
> > to the "max timestamp" semantics.
> >
> >
> >  So we do rely on coprocessors, but the underlying APIs were accessing on
> >> the server-side are pretty light.
> >>
> >>   TLDR? Let's continue in the JIRA?
> >>
> >>>
> >>>>
> >>> Mailing list is fine by me for while we get this hashed out :). We can
> >>> move to Jira when we start getting into specifics.
> >>>
> >>>
> >>
>