Hello Aris, With the latest code adjustments (thank you for that), the library does what supposed to do. For whom may want to try I confirm that it can be integrated as-is in a recent version with a decent effort (it requires a bit of understanding of MonetDB code logic). Here are some remarks/questions I have after checking out a bit the code (from extensibility perspective) and its functionality so far. I am curious if the reason behind a constant MOSAICMAXCNT used for all types is related to thetaselects or projections implementations (do the blocks need to have the counters aligned?). Truth is that for most of the compressing techniques I’ve look into (not from MOSAIC project, but lz4, zstd, blosc2 as general compressors, zp, sz for floating numbers, Daniel Lemire’s compression for integers, dictionaries Judy, Art for strings) the size of the to-be-compressed block is usually the one that matters the most. Block sizes that would fit in L1, L2, L3 cache usually provide better results for certain compressors. Sure, a constant block counter matters per BAT, but would be a problem to have for instance something like MOSAICMAXCNT/(sizeof(type) or twidth ) ? MOSAIC pipe optimizer, being derived from sequential one, will inherit the performance penalties of the latest, yet after I checked the results of mosaic.analysis, I am not even sure that those with a factor close to 1 were actually considered for compression ( I guess RAW alternative is used if gain is under certain threshold) therefore I have no clue how reliable the testing benchmarks are (for those cases do I mostly test RAW codec?). Anyway, for what I have tested. times seem to roughly double when mosaic pipe is used, being only slightly slower than sequential_pipe. I assume that a complex, constant size header for all compressions ( MOSAICHEADER) is convenient to maintain, but I am wondering how that will look if more compressors are about to be added. Is it mandatory to have common header size for all mosaic heaps? Thank you, On Wed, Sep 11, 2019 at 1:53 PM Daniel Zvinca wrote:

Thank you so much for your answer, Aris.

The good news is that compression is considered and is going to be part of MonetDB in two releases or so (one year).

I will try to see if I can use the current code in a custom build, I am quite curious how that will affect performance. To be honest I don't expect performance issues, nowadays even on SSD era, it is still faster to read compressed data and decompress in memory if the right ratio is there, of course. And I do expect decent compression ratio on most of the data.

However, at this stage the MOSAIC's dual compressed - uncompressed storage will obviously not give me the gain I need. Yet, it is interesting to understand at least how query performance might look in the future.

Bad news is of course the compression feature is going to happen in ... one year. But if it comes also with support for compressing in memory results (I know, it wasnt promised), it might worth to wait.

Best regards,

On Wed, Sep 11, 2019 at 12:18 PM aris wrote:

...

-------- Forwarded Message -------- Subject: Re: ALTER TABLE ALTER COLUMN SET STORAGE Date: Tue, 10 Sep 2019 15:15:09 +0200 From: aris To: developers-list-request@monetdb.org

Hi Daniel,

On 10-09-19 12:00, developers-list-request@monetdb.org wrote:

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Today's Topics:

1. ALTER TABLE ALTER COLUMN SET STORAGE (Daniel Zvinca)

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Message: 1 Date: Tue, 10 Sep 2019 12:40:22 +0300 From: Daniel Zvinca To: developers-list@monetdb.org Subject: ALTER TABLE ALTER COLUMN SET STORAGE Message-ID: Content-Type: text/plain; charset="utf-8"

Hello,

I am interested to find out more about ALTER TABLE ALTER COLUMN SET STORAGE feature and how is that related to compression.

As far as I understood this is related to an active development branch, called MOSAIC which was never merged with any of the previous MonetDB versions. Obviously, compression is an important feature columnar databases are providing for data storage and manipulation. A module like MOSAIC that seems to allow several compression techniques, would be an interesting option.

Yes, compression a.k.a. Mosaic is a going to be a new feature in MonetDB. Although the feature won't be included in the upcoming November release. Most likely, you can expect the feature in the first release after the November release. But Mosaic is a somewhat big undertaking. our current road map is probably covering multiple future MonetDB releases before all envisioned compression features are available in MonetDB. The first milestone in the current road map is to apply a single compression technique on an entire column. But one of the next milestone is to partition a column into variable-sized compression blocks. Within each block a particular compression is applied.

First question I have: Can MOSAIC extension be used (sources added and custom compiled) with success for any of its proposed codecs with any of the newest versions (Apr2019 +). I mean without affecting any of embedded, capi, rapi and pyapi modules, which all exchange data with external libraries.

If by this you mean you want to import the mosaic module as an external library into an existing release out of the box, then the answer is no. There are some slight modifications in the GDK layer to accommodate the Mosaic module. And to interact with it from SQL, there are also some code changes in the SQL layer. But besides those dependencies, I don't expect any issue with the particular (x)api frameworks. But nothing is guaranteed obviously. It sounds like you want to hack-back port it into custom builds of earlier releases. I wouldn't give it a zero change of success but I do wish you much luck :)

A quick read of MOSAIC code made me understand that this compression can be applied only on readonly PERSISTENT columns. That means that I would loose the major benefit of compression that I mostly need during importing stage. Sure I can imagine a controlled batching import scheme that would append data to tables and when it reaches certain threshold table is made readonly, then compressed, then added to a merged table, but this looks quite of a scenario. Am I wrong, can MOSAIC be used in a different scenario?

Your observation about the joint life cycle of a Mosaic structure and its original column file is correct: currently Mosaic adds a compressed representation next to the existing uncompressed column. For the first milestone on the Mosaic road map we want to successfully apply compression on READ-ONLY pre-existing columns where the purpose of compression is to potentially accelerate analytical queries on these columns. However we are still looking into potentially freeing the uncompressed column once a compressed Mosaic heap is available. This would accommodate compression for the more traditional sake of limiting memory- and/or disk footprint.

I can understand reasons behind compressing only PERSISTENT bats, yet I am wondering if TRANSIENT bats can also benefit from it especially for 1. result building stage (server-client or embedded version) or 2. for remote connections when data is transferred for merging operations.

Regarding to above question, are there any chances that you would consider keeping compressed results in memory? Sure I can use instead disk temporary tables for subsequent manipulation, but for performance reasons in memory compressed results would be way faster. Actually, when embedded version provides a result set, it stays valid till the user releases it, why not to be able to also use that for possible subsequent SQL operations that do not fit into a CTE scenario. That would provide superior flexibility and memory management to CTE mechanism. Temporary results can be developed in steps, they can be accessed directly at any time as convenient as temporary views in CTE, but without the burden of possible temporary bats that are not released till one CTE ends.

I think it is an interesting idea. But I think it is part of a more general goal/problem of how to handle updates on compressed data. There are internal discussions on this topic. But whatever the outcome, this will be only relevant for a much later milestone on the road map.

Thank you, Dan

Hope it helps.

Kind regards,

Aris