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A snowflake is a single ice crystal that has achieved a sufficient size, and may have amalgamated with others, which falls through the Earth's atmosphere as snow.[1][2][3] Each flake nucleates around a tiny particle in supersaturated air masses by attracting supercooled cloud water droplets, which freeze and accrete in crystal form. Complex shapes emerge as the flake moves through differing temperature and humidity zones in the atmosphere, such that individual snowflakes differ in detail from one another, but may be categorized in eight broad classifications and at least 80 individual variants. The main constituent shapes for ice crystals, from which combinations may occur, are needle, column, plate, and rime. Snow appears white in color despite being made of clear ice. This is due to diffuse reflection of the whole spectrum of light by the small crystal facets of the snowflakes.[4]

Although ice by itself is clear, snow usually appears white in color due to diffuse reflection of the whole spectrum of light by the scattering of light by the small crystal facets of the snowflakes of which it is comprised.[4]

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Although snowflakes are never perfectly symmetrical, the growth of a non-aggregated snowflake often approximates six-fold radial symmetry, arising from the hexagonal crystalline structure of ice.[14] At that stage, the snowflake has the shape of a minute hexagon. The six "arms" of the snowflake, or dendrites, then grow independently from each of the corners of the hexagon, while either side of each arm grows independently. The microenvironment in which the snowflake grows changes dynamically as the snowflake falls through the cloud and tiny changes in temperature and humidity affect the way in which water molecules attach to the snowflake. Since the micro-environment (and its changes) are very nearly identical around the snowflake, each arm tends to grow in nearly the same way. However, being in the same micro-environment does not guarantee that each arm grows the same; indeed, for some crystal forms it does not because the underlying crystal growth mechanism also affects how fast each surface region of a crystal grows.[15] Empirical studies suggest less than 0.1% of snowflakes exhibit the ideal six-fold symmetric shape.[16] Very occasionally twelve branched snowflakes are observed; they maintain the six-fold symmetry.[17]

Snowflakes form in a wide variety of intricate shapes, leading to the notion that "no two are alike". Although nearly-identical snowflakes have been made in laboratory, they are very unlikely to be found in nature.[19][11][20][21] Initial attempts to find identical snowflakes by photographing thousands of them with a microscope from 1885 onward by Wilson Alwyn Bentley found the wide variety of snowflakes we know about today.

The snowflake is often a traditional seasonal image or motif used around the Christmas season, especially in Europe and North America. As a Christian celebration, Christmas celebrates the incarnation of Jesus, who according to Christian belief atones for the sins of humanity; so, in European and North American Christmas traditions, snowflakes symbolize purity.[29][30] Snowflakes are also traditionally associated with the "White Christmas" weather that often occurs during Christmastide.[30] During this period, it is quite popular to make paper snowflakes by folding a piece of paper several times, cutting out a pattern with scissors and then unfolding it.[31][32] The Book of Isaiah refers to the atonement of sins causing them to appear "white as snow" before God (cf. Isaiah 1:18);[30]

Snowflakes are also often used as symbols representing winter or cold conditions. For example, snow tires which enhance traction during harsh winter driving conditions are labelled with a snowflake on the mountain symbol.[33] A stylized snowflake has been part of the emblem of the 1968 Winter Olympics, 1972 Winter Olympics, 1984 Winter Olympics, 1988 Winter Olympics, 1998 Winter Olympics and 2002 Winter Olympics.[34][35]

The first problem with a snowflake server is that it's difficult to reproduce. Should your hardware start having problems, this means that it's difficult to fire up another server to support the same functions. If you need to run a cluster, you get difficulties keeping all of the instances of the cluster in sync. You can't easily mirror your production environment for testing. When you get production faults, you can't investigate them by reproducing the transaction execution in a development environment. [1]

The true fragility of snowflakes, however, comes when you need to change them. Snowflakes soon become hard to understand and modify. Upgrades of one bit software cause unpredictable knock-on effects. You're not sure what parts of the configuration are important, or just the way it came out of the box many years ago. Their fragility leads to long, stressful bouts of debugging. You need manual processes and documentation to support any audit requirements. This is one reason why you often see important software running on ancient operating systems.

A good way to avoid snowflakes is to hold the entire operating configuration of the server in some form of automated recipe. Two tools that have become very popular for this recently are Puppet and Chef. Both allow you to define the operating environment in a form of DomainSpecificLanguage, and easily apply it to a given system.

Application deployment should follow a similar approach: fully automated, all changes in version control. By avoiding snowflakes, it's much easier to have test environments be true clones of production, reducing production bugs caused by configuration differences.

The Visible Ops Handbook is the pioneering book that talked about the dangers of snowflakes and how to avoid them. Continuous Delivery talks about how this approach is a necessary part of a sane build and delivery process. True artists, however, prefer snowflakes.

Depending on the data type in snowflake for the ObjectID, you are seeing expected behavior with the ObjectID being mapped to Double. To overcome this, you can look into using the CAST operation in your SELECT query

I am not sure I understand the need to use "Select by Attributes". Based on our doc, you would not be able to use CAST to convert to an Integer, since Pro does not map any of the supported snowflake datatypes to integer.

The client_session_keep_alive feature is intended to keep Snowflake sessions alive beyond the typical 4 hour timeout limit. The snowflake-connector-python implementation of this feature can prevent processes that use it (read: dbt) from exiting in specific scenarios. If you encounter this in your deployment of dbt, please let us know in the GitHub issue, and work around it by disabling the keepalive.

The retry_on_database_errors flag along with the connect_retries count specification is intended to make retries configurable after the snowflake connector encounters errors of type snowflake.connector.errors.DatabaseError. These retries can be helpful for handling errors of type "JWT token is invalid" when using key pair authentication.

If like me you plan to make this for Christmas morning, you can form the snowflake on Christmas Eve, pop it in the fridge and let it sit overnight. In the morning, remove the snowflake from the fridge and let it sit at room temperature while the oven preheats, then just bake and eat!

I am trying to migrate data from sql server to snowflake.I created a table with an autoincrement column in snowflake so that when i push the data from sql i get an identity column.But after the first load when i tried to load the data again i could see that the values in the identity column is starting from some random place and not from where i expected.I tried with sequence also but still same issue.When i inserted 40 records into to the table i could see the identity column having values from 1 to 40.But when i tried to insert another value the sequence started from 118.I am not able to understand this issue.Could anyone help me??

As you may have noticed the dates are shifted by 1 day. The data type in snowflake is of type DATE whereas in R it is of type character. I am not sure what is causing this issue. I initially thought it might be because of timezone so I tried changing timezone in SNOWFLAKE by running the following lines

This 10.0 mm (0.4 inches) monster snowflake holds the Guinness record for the largest snow crystal. A microscope was used to photograph it in four quadrants, which were later digitally recombined. Kenneth Libbrecht hide caption

This 35.33 mm (1.39 inches) snowflake photographed in Stonybrook, NY in 2015 was the largest captured over multiple winters by researchers using a special camera designed to image falling snowflakes. Sandra Yuter hide caption

This 33.6 mm snowflake (1.32 inches), also from Stonybrook, NY in 2015, is typical of aggregates in that it features a variety of snow crystal shapes, from needle-like columns to fuzzy little balls. Sandra Yuter hide caption

That could help explain why,while the Guiness records would have us believe in snowflakes the size of a dinner plate, the biggest she's ever photographed was 35 millimeters across, or about an inch and a half.

Inspired by the beauty of nature, each piece features expertly placed gemstones and diamonds, nestled in hand-formed settings that evoke the playful spirit of a snowflake. With the use of negative space, the stones seem to glow and take center stage.

Full sun or partial shade and soil that does not dry out entirely in summer. In the wild, snowflakes are found in damp meadows and on river banks, so they are a good choice for a spot where the soil is less than perfectly drained. Bulbs are slow to go dormant in summer; wait to cut back until the leaves have yellowed. e24fc04721