81 Matching Annotations
  1. Nov 2022
    1. Learning is defined to be “storage of automated schema in long-term memory.

      How is learning defined by Sweller in 2002? (Metiri Group, Cisco Sytems, 2008) The storage of automated schema in long-term memory

      What term does Sweller define as the "storage of automated schema in long-term memory"?

  2. Oct 2022
    1. one recognizes in the tactile realitythat so many of the cards are on flimsy copy paper, on the verge of disintegration with eachuse.

      Deutsch used flimsy copy paper, much like Niklas Luhmann, and as a result some are on the verge of disintegration through use over time.

      The wear of the paper here, however, is indicative of active use over time as well as potential care in use, a useful historical fact.

  3. Sep 2022
    1. in south australia we've got the hornsdale power reserve which is a 00:32:43 100 megawatt capacity this is one that elon musk very famously uh put in so this is what the european union is now using as the standard to talk about you know it's 00:32:56 been done in australia we can do it here so in the global system we would need 15 million 635 and 478 such stations across the planet 00:33:08 in the power grid system just for that four week buffer so and that is actually about 30 times capacity uh compared to the entire global

      !- for : global capacity renewable energy storage - this is not realistic

  4. Aug 2022
  5. Jul 2022
    1. ```js function formatBytes(bytes, decimals = 2) { if (bytes === 0) return '0 Bytes';

      const k = 1024; const dm = decimals < 0 ? 0 : decimals; const sizes = ['Bytes', 'KB', 'MB', 'GB', 'TB', 'PB', 'EB', 'ZB', 'YB']; const i = Math.floor(Math.log(bytes) / Math.log(k)); return parseFloat((bytes / Math.pow(k, i)).toFixed(dm)) + ' ' + sizes[i]; } ```

  6. Jun 2022
    1. I also like the simplicity of a box. There’s a purpose here, and it has a lot to dowith efficiency. A writer with a good storage and retrieval system can write faster.He isn’t spending a lot of time looking things up, scouring his papers, and patrollingother rooms at home wondering where he left that perfect quote. It’s in the box.

      A card index can be a massive boon to a writer as a well-indexed one, in particular, will save massive amounts of time which might otherwise be spent searching for quotes or ideas that they know they know, but can't easily recreate.

    2. It’s not the only answer, of course. Maurice Sendak has a room that’s theequivalent of my boxes, a working studio that contains a huge unit with flat pulloutdrawers in which he keeps sketches, reference materials, notes, articles. He works onseveral projects at a time, and he likes to keep the overlapping materials out of sightwhen he’s tackling any one of them. Other people rely on carefully arranged indexcards. The more technological among us put it all on a computer. There’s no singlecorrect system. Anything can work, so long as it lets you store and retrieve yourideas—and never lose them.

      Regardless of what sort of physical instantiation one's notes may take, a workable storage option for them is necessary whether it is a simple box, a shelving system, a curiosity cabinet, a flat file, or even an entire room itself.

  7. May 2022
    1. a society-wide hyperconversation. This hyperconversation operationalizes continuous discourse, including its differentiation and emergent framing aspects. It aims to assist people in developing their own ways of framing and conceiving the problem that makes sense given their social, cultural, and environmental contexts. As depicted in table 1, the hyperconversation also reflects a slower, more deliberate approach to discourse; this acknowledges damaged democratic processes and fractured societal social cohesion. Its optimal design would require input from other relevant disciplines and expertise,

      The public Indyweb is eminently designed as a public space for holding deep, continuous, asynchronous conversations with provenance. That is, if the partcipant consents to public conversation, ideas can be publicly tracked. Whoever reads your public ideas can be traced.and this paper trail is immutably stored, allowing anyone to see the evolution of ideas in real time.

      In theory, this does away with the need for patents and copyrights, as all ideas are traceable to the contributors and each contribution is also known. This allows for the system to embed crowdsourced microfunding, supporting the best (upvoted) ideas to surface.

      Participants in the public Indyweb ecosystem are called Indyviduals and each has their own private data hub called an Indyhub. Since Indyweb is interpersonal computing, each person is the center of their indyweb universe. Through the discoverability built into the Indyweb, anything of immediate salience is surfaced to your private hub. No applications can use your data unless you give exact permission on which data to use and how it shall be used. Each user sets the condition for their data usage. Instead of a user's data stored in silos of servers all over the web as is current practice, any data you generate, in conversation, media or data files is immediately accessible on your own Indyhub.

      Indyweb supports symmathesy, the exchange of ideas based on an appropriate epistemological model that reflects how human INTERbeings learn as a dynamic interplay between individual and collective learning. Furthermore, all data that participants choose to share is immutably stored on content addressable web3 storage forever. It is not concentrated on any server but the data is stored on the entire IPFS network:

      "IPFS works through content adddressibility. It is a peer-to-peer (p2p) storage network. Content is accessible through peers located anywhere in the world, that might relay information, store it, or do both. IPFS knows how to find what you ask for using its content address rather than its location.

      There are three fundamental principles to understanding IPFS:

      Unique identification via content addressing Content linking via directed acyclic graphs (DAGs) Content discovery via distributed hash tables (DHTs)" (Source: https://docs.ipfs.io/concepts/how-ipfs-works/)

      The privacy, scalability, discoverability, public immutability and provenance of the public Indyweb makes it ideal for supporting hyperconversations that emerge tomorrows collectively emergent solutions. It is based on the principles of thought augmentation developed by computer industry pioneers such as Doug Englebart and Ted Nelson who many decades earlier in their prescience foresaw the need for computing tools to augment thought and provide the ability to form Network Improvement Communities (NIC) to solve a new generation of complex human challenges.

    1. In explaining his approach, Luhmann emphasized, with the first stepsof computer technology in mind, the benefits of the principle of “multiple storage”: in the card index itserves to provide different avenues of accessing a topic or concept since the respective notes may be filedin different places and different contexts. Conversely, embedding a topic in various contexts gives rise todifferent lines of information by means of opening up different realms of comparison in each case due tothe fact that a note is an information only in a web of other notes. Furthermore it was Luhmann’s intentionto “avoid premature systematization and closure and maintain openness toward the future.”11 His way oforganizing the collection allows for it to continuously adapt to the evolution of his thinking and his overalltheory which as well is not conceptualized in a hierarchical manner but rather in a cybernetical way inwhich every term or theoretical concept is dependent on the other.

      While he's couching it in the computer science milieu of his day, this is not dissimilar to the Llullan combinatorial arts.

    1. Also, keep in mind that you don’t need to find a single app to fulfill all your needs. You might use more than one tool at a time depending on the use case.

      It's true that each note taking application may be purpose fit for a particular use, but having a single store for all of your notes is incredibly important for future search and re-discovery. Keeping one's notes across a range of applications is disaster waiting to happen, at least until there is a bigger aggregate search function that can search across multiple platforms.

  8. Apr 2022
  9. Mar 2022
    1. The steel tower is a giant mechanical energy storage system, designed by American-Swiss startup Energy Vault, that relies on gravity and 35-ton bricks to store and release energy.

      Like pumped hydro with rocks

  10. Feb 2022
  11. Jan 2022
  12. Dec 2021
    1. Edge computing is an emerging new trend in cloud data storage that improves how we access and process data online. Businesses dealing with high-frequency transactions like banks, social media companies, and online gaming operators may benefit from edge computing.

      Edge Computing: What It Is and Why It Matters0 https://en.itpedia.nl/2021/12/29/edge-computing-what-it-is-and-why-it-matters/ Edge computing is an emerging new trend in cloud data storage that improves how we access and process data online. Businesses dealing with high-frequency transactions like banks, social media companies, and online gaming operators may benefit from edge computing.

    1. Here, I also briefl y digress and examine two coinciding addressing logics: In the same decade and in the same town, the origin of the card index cooccurs with the invention of the house number. This establishes the possibility of abstract representation of (and controlled access to) both texts and inhabitants.

      Curiously, and possibly coincidently, the idea of the index card and the invention of the house number co-occur in the same decade and the same town. This creates the potential of abstracting the representation of information and people into numbers for easier access and linking.

  13. Nov 2021
    1. wn oral cultures the sorting function canbe performedW for exampleW by integration into a narrative Sstorytelling orbardic poetryTY

      The sorting function is also done by mental links from one space to another similar to the method of loci in Western culture. cross reference the idea of songlines

    2. ́herange of storage media operative in different historical contexts includesthe marked stone tokenW the clay tabletW the knotted cord or quipuW the paX

      pyrus scroll and the sheet of parchment.

      Which others is she missing from a mnemonics perspective? I'm impressed that she indicates the khipu, but there are certainly other indigenous methods from oral cultures.

  14. Sep 2021
    1. In building this system we simultaneously solved three high-level challenges: supporting exabyte-scale, isolating performance between tenants, and enabling tenant-specific optimizations. Exabyte-scale clusters are important for operational simplicity and resource sharing. Tectonic disaggregates the file system metadata into independently scalable layers, and hash-partitions each metadata layer into a scalable shared key-value store. Combined with a linearly scalable storage node layer, this disaggregated metadata allows the system to meet the storage needs of an entire data center.

      So, it seems to add a layer of indirection, so instead of everyone needing to read off the same bits of a disk, the data is stored in places indexed by the KV store, which allows reads and writes to be spread across a linearly scaling storage layer.

      Worth reading the paper to check if this guess is close to reality

    1. When salvinorin A isolated from leaves of Salvia divinorum was irradiated with 300 nm UV light in ethyl acetate, it degraded from 100 μg/mL to 2.84 ± 0.05 μg/mL in 30 min. The calculated average rate constant k of this degradation was 0.12/min and the half-life was 5.7 min. When authentic salvinorin A was irradiated by UV light in an organic solution or an aqueous solution, it degraded over 90% within 40 min, whereas when it was irradiated by natural sunlight, it took 8 h to degrade 50% both in an organic and an aqueous solution.

      Incredible. I may have destroyed my current batch. I'll have to start over. Good thing I only made a moderate amount.

    1. Warehouse Storage Solutions - Connect Warehouse

      Welcome to Connect Warehouse Storage Solutions. We are experts in providing professional storage services, including eCommerce warehouse storage solutions, pallet storage, container de-stuffing, and more.

      We pride ourselves on delivering safe, secure, and cost-effective eCommerce warehouse storage and industrial storage solutions, and have been doing so for customers around the world for many years. Our expert team of staff is well trained and experienced, and our facility is state of the art.

      All in all, we are confident that we understand the complexities of warehouse storage better than anyone, making us your ideal industrial storage solutions partner.

      Our Warehouse Commercial Storage Solutions Facility

      When you choose Connect, you’re choosing versatility, modernity, and efficiency for your storage requirements. Our brilliant facility features heavy-duty racking, highly trained staff, advanced technology, and onsite security to make sure that all of your goods are safe and sound in a professional environment.

      All of this is set up to help ensure maximum safety for your inventory and more control for you, so you have peace of mind every step of the way that your goods are in safe hands.

      Within our facility, we provide an eclectic mix of different industrial storage provisions, with something to suit every requirement. Let’s take a look at some of the different kinds of provisions we handle at Connect and see how we can help you with all of your storage needs today.

      industrial storage solutions uk

    1. Connect Pallet Storage Warehouse

      Pallet Storage with Connect Welcome to Connect Pallet Storage. Here at Connect, we provide the best of the best when it comes to pallet storage and have been doing so for national and international customers for a number of years.

      ​We’ve built up a strong reputation over the years for our attention to detail and beautifully kept, high-quality pallet storage warehouse facility. And it is here where we can help your business thrive, no matter what it is you do or what it is you require when it comes to pallet storage.

      Racked Pallet Storage Our pallet storage warehouse features high-quality, durable racked storage for your pallet storage requirements.

      We have over 4,500 pallet spaces available in our fully racked warehouse and provide a safe and secure space for your cargo.

      pallet storage warehouse

  15. Jul 2021
    1. By making the storage and organization of information everyone’s responsibility and no one’s, the internet and web could grow, unprecedentedly expanding access, while making any and all of it fragile rather than robust in many instances in which we depend on it.
    1. This system was invented by Carl Linnaeus,[1] around 1760.

      How is it not so surprising that Carl Linnaeus, the creator of a huge taxonomic system, also came up with the idea for index cards in 1760.

      How does this fit into the history of the commonplace book and information management? Relationship to the idea of a zettelkasten?

  16. Apr 2021
    1. Preferences DataStore and Proto DataStore DataStore provides two different implementations: Preferences DataStore and Proto DataStore. Preferences DataStore stores and accesses data using keys. This implementation does not require a predefined schema, and it does not provide type safety. Proto DataStore stores data as instances of a custom data type. This implementation requires you to define a schema using protocol buffers, but it provides type safety.

      Currently, I am using SharedPreference which is still alright to use. However, there is a better option called DataStore. This allows data to be stored asynchronously.

    1. What about seed banks? There have been efforts to try to ensure that not only the most popular seeds survive. Let’s call these seed banks, where the more rare gems are maintained and passed on as generational wealth.
  17. Mar 2021
    1. nucleus accumbens

      RESEARCH MORE. What is this? What it's role in memory storage?

    2. Now, where the emotional memory is stored in response to these survival-enhancing positive memories is not yet entirely clear.

      I have heard this from several of my sources. This one is a bit more dated than some of the others I've used, so I need to look at something more recent and see if this has changed.

  18. Dec 2020
    1. class Session extends Map { set(id, value) { if (typeof value === 'object') value = JSON.stringify(value); sessionStorage.setItem(id, value); } get(id) { const value = sessionStorage.getItem(id); try { return JSON.parse(value); } catch (e) { return value; } } }
    2. I think that the webStorage is one of the most exciting improvement of the new web. But save only strings in the value key-map I think is a limitation.
    1. This is the accepted way to handle problems related to authentication, because user data has a couple of important characteristics: You really don't want to accidentally leak it between two sessions on the same server, and generating the store on a per-request basis makes that very unlikely It's often used in lots of different places in your app, so a global store makes sense.
  19. Nov 2020
    1. The real heart of the matter of selection, however, goes deeper than a lag in the adoption of mechanisms by libraries, or a lack of development of devices for their use. Our ineptitude in getting at the record is largely caused by the artificiality of systems of indexing. When data of any sort are placed in storage, they are filed alphabetically or numerically, and information is found (when it is) by tracing it down from subclass to subclass. It can be in only one place, unless duplicates are used; one has to have rules as to which path will locate it, and the rules are cumbersome. Having found one item, moreover, one has to emerge from the system and re-enter on a new path.

      Bush emphasises the importance of retrieval in the storage of information. He talks about technical limitations, but in this paragraph he stresses that retrieval is made more difficult by the "artificiality of systems of indexing", in other words, our default file-cabinet metaphor for storing information.

      Information in such a hierarchical architecture is found by descending down into the hierarchy, and back up again. Moreover, the information we're looking for can only be in one place at a time (unless we introduce duplicates).

      Having found our item of interest, we need to ascend back up the hierarchy to make our next descent.

    2. So much for the manipulation of ideas and their insertion into the record. Thus far we seem to be worse off than before—for we can enormously extend the record; yet even in its present bulk we can hardly consult it. This is a much larger matter than merely the extraction of data for the purposes of scientific research; it involves the entire process by which man profits by his inheritance of acquired knowledge. The prime action of use is selection, and here we are halting indeed. There may be millions of fine thoughts, and the account of the experience on which they are based, all encased within stone walls of acceptable architectural form; but if the scholar can get at only one a week by diligent search, his syntheses are not likely to keep up with the current scene.

      Retrieval is the key activity we're interested in. Storage only matters in as much as we can retrieve effectively. At the time of writing (1945) large amounts of information could be stored (extend the record), but consulting that record was still difficult.

  20. Oct 2020
  21. Sep 2020
    1. This impacts monetization and purchasing at companies. Paying for a new design tool because it has new features for designers may not be a top priority. But if product managers, engineers, or even the CEO herself think it matters for the business as a whole—that has much higher priority and pricing leverage.

      If a tool benefits the entire team, vs. just the designer, it becomes an easier purchase decision.

  22. Jul 2020
    1. A key strength of OnlyOffice is its cloud-based storage options, which let you connect your Google Drive, Dropbox, Box, OneDrive, and Yandex.Disk accounts.
  23. Jun 2020
    1. However, when you use an SD card as internal storage, Android formats the SD card in such a way that no other device can read it. Android also expects the adopted SD card to always be present, and won’t work quite right if you remove it.
  24. May 2020
    1. Your Amazon Athena query performance improves if you convert your data into open source columnar formats, such as Apache Parquet

      s3 perfomance use columnar formats

    1. Available Internet Connection Theoretical Min. Number of Days to Transfer 100TB at 80% Network Utilization When to Consider AWS Snowball? T3 (44.736Mbps) 269 days 2TB or more 100Mbps 120 days 5TB or more 1000Mbps 12 days 60TB or more

      when snowball

      1000Mbps 12 days 60TB

  25. Apr 2020
    1. Data Erasure and Storage Time The personal data of the data subject will be erased or blocked as soon as the purpose of storage ceases to apply. The data may be stored beyond that if the European or national legislator has provided for this in EU regulations, laws or other provisions to which the controller is subject. The data will also be erased or blocked if a storage period prescribed by the aforementioned standards expires, unless there is a need for further storage of the data for the conclusion or performance of a contract.
  26. Mar 2020
    1. I would like to make an appeal to core developers: all design decisions involving involuntary session creation MUST be made with a great caution. In case of a high-load project, avoiding to create a session for non-authenticated users is a vital strategy with a critical influence on application performance. It doesn't really make a big difference, whether you use a database backend, or Redis, or whatever else; eventually, your load would be high enough, and scaling further would not help anymore, so that either network access to the session backend or its “INSERT” performance would become a bottleneck. In my case, it's an application with 20-25 ms response time under a 20000-30000 RPM load. Having to create a session for an each session-less request would be critical enough to decide not to upgrade Django, or to fork and rewrite the corresponding components.
  27. Feb 2020
  28. Jan 2020
  29. Dec 2019
    1. Practical highlights in my opinion:

      • It's important to know about data padding in PG.
      • Be conscious when modelling data tables about columns ordering, but don't be pure-school and do it in a best-effort basis.
      • Gains up to 25% in wasted storage are impressive but always keep in mind the scope of the system. For me, gains are not worth it in the short-term. Whenever a system grows, it is possible to migrate data to more storage-efficient tables but mind the operative burder.

      Here follows my own commands on trying the article points. I added - pg_column_size(row()) on each projection to have clear absolute sizes.

      -- How does row function work?
      
      SELECT pg_column_size(row()) AS empty,
             pg_column_size(row(0::SMALLINT)) AS byte2,
             pg_column_size(row(0::BIGINT)) AS byte8,
             pg_column_size(row(0::SMALLINT, 0::BIGINT)) AS byte16,
             pg_column_size(row(''::TEXT)) AS text0,
             pg_column_size(row('hola'::TEXT)) AS text4,
             0 AS term
      ;
      
      -- My own take on that
      
      SELECT pg_column_size(row()) AS empty,
             pg_column_size(row(uuid_generate_v4())) AS uuid_type,
             pg_column_size(row('hola mundo'::TEXT)) AS text_type,
             pg_column_size(row(uuid_generate_v4(), 'hola mundo'::TEXT)) AS uuid_text_type,
             pg_column_size(row('hola mundo'::TEXT, uuid_generate_v4())) AS text_uuid_type,
             0 AS term
      ;
      
      CREATE TABLE user_order (
        is_shipped    BOOLEAN NOT NULL DEFAULT false,
        user_id       BIGINT NOT NULL,
        order_total   NUMERIC NOT NULL,
        order_dt      TIMESTAMPTZ NOT NULL,
        order_type    SMALLINT NOT NULL,
        ship_dt       TIMESTAMPTZ,
        item_ct       INT NOT NULL,
        ship_cost     NUMERIC,
        receive_dt    TIMESTAMPTZ,
        tracking_cd   TEXT,
        id            BIGSERIAL PRIMARY KEY NOT NULL
      );
      
      SELECT a.attname, t.typname, t.typalign, t.typlen
        FROM pg_class c
        JOIN pg_attribute a ON (a.attrelid = c.oid)
        JOIN pg_type t ON (t.oid = a.atttypid)
       WHERE c.relname = 'user_order'
         AND a.attnum >= 0
       ORDER BY a.attnum;
      
      -- What is it about pg_class, pg_attribute and pg_type tables? For future investigation.
      
      -- SELECT sum(t.typlen)
      -- SELECT t.typlen
      SELECT a.attname, t.typname, t.typalign, t.typlen
        FROM pg_class c
        JOIN pg_attribute a ON (a.attrelid = c.oid)
        JOIN pg_type t ON (t.oid = a.atttypid)
       WHERE c.relname = 'user_order'
         AND a.attnum >= 0
       ORDER BY a.attnum
      ;
      
      -- Whoa! I need to master mocking data directly into db.
      
      INSERT INTO user_order (
          is_shipped, user_id, order_total, order_dt, order_type,
          ship_dt, item_ct, ship_cost, receive_dt, tracking_cd
      )
      SELECT true, 1000, 500.00, now() - INTERVAL '7 days',
             3, now() - INTERVAL '5 days', 10, 4.99,
             now() - INTERVAL '3 days', 'X5901324123479RROIENSTBKCV4'
        FROM generate_series(1, 1000000);
      
      -- New item to learn, pg_relation_size. 
      
      SELECT pg_relation_size('user_order') AS size_bytes,
             pg_size_pretty(pg_relation_size('user_order')) AS size_pretty;
      
      SELECT * FROM user_order LIMIT 1;
      
      SELECT pg_column_size(row(0::NUMERIC)) - pg_column_size(row()) AS zero_num,
             pg_column_size(row(1::NUMERIC)) - pg_column_size(row()) AS one_num,
             pg_column_size(row(9.9::NUMERIC)) - pg_column_size(row()) AS nine_point_nine_num,
             pg_column_size(row(1::INT2)) - pg_column_size(row()) AS int2,
             pg_column_size(row(1::INT4)) - pg_column_size(row()) AS int4,
             pg_column_size(row(1::INT2, 1::NUMERIC)) - pg_column_size(row()) AS int2_one_num,
             pg_column_size(row(1::INT4, 1::NUMERIC)) - pg_column_size(row()) AS int4_one_num,
             pg_column_size(row(1::NUMERIC, 1::INT4)) - pg_column_size(row()) AS one_num_int4,
             0 AS term
      ;
      
      SELECT pg_column_size(row(''::TEXT)) - pg_column_size(row()) AS empty_text,
             pg_column_size(row('a'::TEXT)) - pg_column_size(row()) AS len1_text,
             pg_column_size(row('abcd'::TEXT)) - pg_column_size(row()) AS len4_text,
             pg_column_size(row('abcde'::TEXT)) - pg_column_size(row()) AS len5_text,
             pg_column_size(row('abcdefgh'::TEXT)) - pg_column_size(row()) AS len8_text,
             pg_column_size(row('abcdefghi'::TEXT)) - pg_column_size(row()) AS len9_text,
             0 AS term
      ;
      
      SELECT pg_column_size(row(''::TEXT, 1::INT4)) - pg_column_size(row()) AS empty_text_int4,
             pg_column_size(row('a'::TEXT, 1::INT4)) - pg_column_size(row()) AS len1_text_int4,
             pg_column_size(row('abcd'::TEXT, 1::INT4)) - pg_column_size(row()) AS len4_text_int4,
             pg_column_size(row('abcde'::TEXT, 1::INT4)) - pg_column_size(row()) AS len5_text_int4,
             pg_column_size(row('abcdefgh'::TEXT, 1::INT4)) - pg_column_size(row()) AS len8_text_int4,
             pg_column_size(row('abcdefghi'::TEXT, 1::INT4)) - pg_column_size(row()) AS len9_text_int4,
             0 AS term
      ;
      
      SELECT pg_column_size(row(1::INT4, ''::TEXT)) - pg_column_size(row()) AS int4_empty_text,
             pg_column_size(row(1::INT4, 'a'::TEXT)) - pg_column_size(row()) AS int4_len1_text,
             pg_column_size(row(1::INT4, 'abcd'::TEXT)) - pg_column_size(row()) AS int4_len4_text,
             pg_column_size(row(1::INT4, 'abcde'::TEXT)) - pg_column_size(row()) AS int4_len5_text,
             pg_column_size(row(1::INT4, 'abcdefgh'::TEXT)) - pg_column_size(row()) AS int4_len8_text,
             pg_column_size(row(1::INT4, 'abcdefghi'::TEXT)) - pg_column_size(row()) AS int4_len9_text,
             0 AS term
      ;
      
      SELECT pg_column_size(row()) - pg_column_size(row()) AS empty_row,
             pg_column_size(row(''::TEXT)) - pg_column_size(row()) AS no_text,
             pg_column_size(row('a'::TEXT)) - pg_column_size(row()) AS min_text,
             pg_column_size(row(1::INT4, 'a'::TEXT)) - pg_column_size(row()) AS two_col,
             pg_column_size(row('a'::TEXT, 1::INT4)) - pg_column_size(row()) AS round4;
      
      SELECT pg_column_size(row()) - pg_column_size(row()) AS empty_row,
             pg_column_size(row(1::SMALLINT)) - pg_column_size(row()) AS int2,
             pg_column_size(row(1::INT)) - pg_column_size(row()) AS int4,
             pg_column_size(row(1::BIGINT)) - pg_column_size(row()) AS int8,
             pg_column_size(row(1::SMALLINT, 1::BIGINT)) - pg_column_size(row()) AS padded,
             pg_column_size(row(1::INT, 1::INT, 1::BIGINT)) - pg_column_size(row()) AS not_padded;
      
      SELECT a.attname, t.typname, t.typalign, t.typlen
        FROM pg_class c
        JOIN pg_attribute a ON (a.attrelid = c.oid)
        JOIN pg_type t ON (t.oid = a.atttypid)
       WHERE c.relname = 'user_order'
         AND a.attnum >= 0
       ORDER BY t.typlen DESC;
      
      DROP TABLE user_order;
      
      CREATE TABLE user_order (
        id            BIGSERIAL PRIMARY KEY NOT NULL,
        user_id       BIGINT NOT NULL,
        order_dt      TIMESTAMPTZ NOT NULL,
        ship_dt       TIMESTAMPTZ,
        receive_dt    TIMESTAMPTZ,
        item_ct       INT NOT NULL,
        order_type    SMALLINT NOT NULL,
        is_shipped    BOOLEAN NOT NULL DEFAULT false,
        order_total   NUMERIC NOT NULL,
        ship_cost     NUMERIC,
        tracking_cd   TEXT
      );
      
      -- And, what about other varying size types as JSONB?
      
      SELECT pg_column_size(row('{}'::JSONB)) - pg_column_size(row()) AS empty_jsonb,
             pg_column_size(row('{}'::JSONB, 0::INT4)) - pg_column_size(row()) AS empty_jsonb_int4,
             pg_column_size(row(0::INT4, '{}'::JSONB)) - pg_column_size(row()) AS int4_empty_jsonb,
             pg_column_size(row('{"a": 1}'::JSONB)) - pg_column_size(row()) AS basic_jsonb,
             pg_column_size(row('{"a": 1}'::JSONB, 0::INT4)) - pg_column_size(row()) AS basic_jsonb_int4,
             pg_column_size(row(0::INT4, '{"a": 1}'::JSONB)) - pg_column_size(row()) AS int4_basic_jsonb,
             0 AS term;
      
  30. Oct 2019
    1. Best Overall: SanDisk Extreme PRO 128 GB Drive 3.5 Buy on Amazon The SanDisk PRO gives you blistering speeds, offering 420 MB/s on the reading front and 380 MB/s on the writing end, which is 3–4x faster than what a standard USB 3.0 drive will offer. The sleek, aluminum casing is both super durable and very eye-catching, so you can bring it with you to your business meetings and look professional as well. The onboard AES, 128-bit file encryption gives you top-of-the-line security for your sensitive files.
  31. Apr 2019
    1. When you get started, you get signed up by default for the FREE Gaia storage provided by Blockstack PBC. Yes, that's right, you get FREE encrypted storage.
  32. Feb 2018
  33. Sep 2017
    1. In 2005, the figure had raised to 1%. They are now responsible for more carbon-dioxide emissions per year than Argentina or the Netherlands and, if current trends hold, their emissions will have grown four-fold by 2020, reaching 670m tonnes

      How is information, for example, a conversation accounted for in this model? As we go forward and find more efficient ways to store and convey information in fewer 1s and 0s, must we constantly reevaluate this relationship? Passive vs Active storage of information seems to be key here as well.

  34. Jul 2016
    1. unprecedented accumulation of contemporary data

      this is the storage question everyone always goes to 1st when we use the word "data" in libraries. Is there possibly another question we should ask first?

  35. Apr 2015
    1. Do I own my content on The Grid? Yes, you own your content. The engine AutoDesigns your site, publishes it, and stores it on Github. Your source content will live in a Github repository that you can access and download anytime.

      Is access private/public?

  36. Sep 2014
    1. Fast restart. If a server is temporarily taken down, this capability restores the index from a saved copy, eliminating delays due to index rebuilding.

      This point seems to be in direct contradiction to the claim above that "Indexes (primary and secondary) are always stored in DRAM for fast access and are never stored on Solid State Drives (SSDs) to ensure low wear."

    2. Unlike other databases that use the linux file system that was built for rotational drives, Aerospike has implemented a log structured file system to access flash – raw blocks on SSDs – directly.

      Does this really mean to suggest that Aerospike bypasses the linux block device layer? Is there a kernel driver? Does this mean I can't use any filesystem I want and know how to administrate? Is the claim that the "linux file system" (which I take to mean, I guess, the virtual file system layer) "built for rotation drives" even accurate? We've had ram disks for a long, long time. And before that we've had log structured filesystems, too, and even devices that aren't random access like tape drives. Seems like dubious claims all around.

  37. Jan 2014