Cassandra-Java-Driver-Research | Cassandra java-driver源代码学习研究

 by   codefollower Java Version: Current License: Apache-2.0

kandi X-RAY | Cassandra-Java-Driver-Research Summary

kandi X-RAY | Cassandra-Java-Driver-Research Summary

Cassandra-Java-Driver-Research is a Java library typically used in Big Data, Docker, Hadoop applications. Cassandra-Java-Driver-Research has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Cassandra-Java-Driver-Research
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              Cassandra-Java-Driver-Research has a low active ecosystem.
              It has 30 star(s) with 25 fork(s). There are 6 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 1 open issues and 0 have been closed. On average issues are closed in 1142 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of Cassandra-Java-Driver-Research is current.

            kandi-Quality Quality

              Cassandra-Java-Driver-Research has no bugs reported.

            kandi-Security Security

              Cassandra-Java-Driver-Research has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              Cassandra-Java-Driver-Research is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              Cassandra-Java-Driver-Research releases are not available. You will need to build from source code and install.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.

            Top functions reviewed by kandi - BETA

            kandi has reviewed Cassandra-Java-Driver-Research and discovered the below as its top functions. This is intended to give you an instant insight into Cassandra-Java-Driver-Research implemented functionality, and help decide if they suit your requirements.
            • Main method for testing
            • Sets the core number of connections per host
            • Initialize the csv report file
            • Outputs console to console console
            • Parses a string into a value
            • Returns the index of the first character after the given index
            • Returns the index of a CQL identifier
            • Builds the table definition
            • Validates columns declaration
            • Sets the final result
            • Builds the SQL query string
            • Creates a frame from the given full frame
            • Returns the routing key for this bound query
            • Returns a query plan for the given child policy
            • Builds the query string for the insert statement
            • Sets the default options
            • Builds the UPDATE query string
            • Initialize the internal state of this ClusterManager
            • Returns a query plan for this query
            • Sets the protocol version
            • Runs the reconnection loop
            • Returns a query plan for the given datacenter
            • Returns a query plan for the given query
            • Fetches the node information for a given host
            • Builds the query string
            • Forces a new connection pool for reuse
            Get all kandi verified functions for this library.

            Cassandra-Java-Driver-Research Key Features

            No Key Features are available at this moment for Cassandra-Java-Driver-Research.

            Cassandra-Java-Driver-Research Examples and Code Snippets

            No Code Snippets are available at this moment for Cassandra-Java-Driver-Research.

            Community Discussions

            QUESTION

            How to group unassociated content
            Asked 2022-Apr-15 at 12:43

            I have a hive table that records user behavior

            like this

            userid behavior timestamp url 1 view 1650022601 url1 1 click 1650022602 url2 1 click 1650022614 url3 1 view 1650022617 url4 1 click 1650022622 url5 1 view 1650022626 url7 2 view 1650022628 url8 2 view 1650022631 url9

            About 400GB is added to the table every day.

            I want to order by timestamp asc, then one 'view' is in a group between another 'view' like this table, the first 3 lines belong to a same group , then subtract the timestamps, like 1650022614 - 1650022601 as the view time.

            How to do this?

            i try lag and lead function, or scala like this

            ...

            ANSWER

            Answered 2022-Apr-15 at 12:43

            If you use dataframe, you can build partition by using window that sum a column whose value is 1 when you change partition and 0 if you don't change partition.

            You can transform a RDD to a dataframe with sparkSession.createDataframe() method as explained in this answer

            Back to your problem. In you case, you change partition every time column behavior is equal to "view". So we can start with this condition:

            Source https://stackoverflow.com/questions/71883786

            QUESTION

            Using Spark window with more than one partition when there is no obvious partitioning column
            Asked 2022-Apr-10 at 20:21

            Here is the scenario. Assuming I have the following table:

            identifier line 51169081604 2 00034886044 22 51168939455 52

            The challenge is to, for every single column line, select the next biggest column line, which I have accomplished by the following SQL:

            ...

            ANSWER

            Answered 2022-Apr-10 at 20:21

            Using your "next" approach AND assuming the data is generated in ascending line order, the following does work in parallel, but if actually faster you can tell me; I do not know your volume of data. In any event you cannot solve just with SQL (%sql).

            Here goes:

            Source https://stackoverflow.com/questions/71803991

            QUESTION

            What is the best way to store +3 millions records in Firestore?
            Asked 2022-Apr-09 at 13:18

            I want to store +3 millions records in my Firestore database and I would like to know what is the best way, practice, to do that.

            In fact, I want to store every prices of 30 cryptos every 15 minutes since 01/01/2020.

            For example:

            • ETH price at 01/01/2020 at 00h00 = xxx
            • ETH price at 01/01/2020 at 00h15 = xxx
            • ETH price at 01/01/2020 at 00h30 = xxx
            • ...
            • ETH price at 09/04/2022 at 14h15 = xxx

            and this, for 30 cryptos (or more).

            So, 120 prices per day multiplied by 829 days multiplied by 30 cryptos ~= 3M records

            I thought of saving this like this:

            [Collection of Crypto] [Document of crypto] [Collection of dates] [Document of hour] [Price]

            I don't know if this is the right way, that's why I come here :)

            Of course, the goal of this database will be to retrieve ALL the historical prices of a currency that I would have selected. This will allow me to make statistics etc later.

            Thanks for your help

            ...

            ANSWER

            Answered 2022-Apr-09 at 13:18

            For the current structure, instead of creating a document every 15 minutes you can just create a "prices" document and store an array of format { time: "00:00", price: 100 } which will cost only 1 read to fetch prices of a given currency on a day instead of 96.

            Alternatively, you can create a single collection "prices" and create a document everyday for each currency. A document in this collection can look like this:

            Source https://stackoverflow.com/questions/71808107

            QUESTION

            spark-shell throws java.lang.reflect.InvocationTargetException on running
            Asked 2022-Apr-01 at 19:53

            When I execute run-example SparkPi, for example, it works perfectly, but when I run spark-shell, it throws these exceptions:

            ...

            ANSWER

            Answered 2022-Jan-07 at 15:11

            i face the same problem, i think Spark 3.2 is the problem itself

            switched to Spark 3.1.2, it works fine

            Source https://stackoverflow.com/questions/70317481

            QUESTION

            For function over multiple rows (i+1)?
            Asked 2022-Mar-30 at 08:31

            New to R, my apologies if there is an easy answer that I don't know of.

            I have a dataframe with 127.124 observations and 5 variables

            Head(SortedDF)

            ...

            ANSWER

            Answered 2022-Mar-30 at 08:31
            library(tidyverse)
            
            data <- tibble(x = c(1, 1, 2), y = "a")
            data
            #> # A tibble: 3 × 2
            #>       x y    
            #>    
            #> 1     1 a    
            #> 2     1 a    
            #> 3     2 a
            
            same_rows <-
              data %>%
              # consider all columns
              unite(col = "all") %>%
              transmute(same_as_next_row = all == lead(all))
            
            data %>%
              bind_cols(same_rows)
            #> # A tibble: 3 × 3
            #>       x y     same_as_next_row
            #>                
            #> 1     1 a     TRUE            
            #> 2     1 a     FALSE           
            #> 3     2 a     NA
            

            Source https://stackoverflow.com/questions/71673259

            QUESTION

            Filling up shuffle buffer (this may take a while)
            Asked 2022-Mar-28 at 20:44

            I have a dataset that includes video frames partially 1000 real videos and 1000 deep fake videos. each video after preprocessing phase converted to the 300 frames in other worlds I have a dataset with 300000 images with Real(0) label and 300000 images with Fake(1) label. I want to train MesoNet with this data. I used costum DataGenerator class to handle train, validation, test data with 0.8,0.1,0.1 ratios but when I run the project show this message:

            ...

            ANSWER

            Answered 2021-Nov-10 at 14:23

            QUESTION

            Designing Twitter Search - How to sort large datasets?
            Asked 2022-Mar-24 at 17:25

            I'm reading an article about how to design a Twitter Search. The basic idea is to map tweets based on their ids to servers where each server has the mapping

            English word -> A set of tweetIds having this word

            Now if we want to find all the tweets that have some word all we need is to query all servers and aggregate the results. The article casually suggests that we can also sort the results by some parameter like "popularity" but isn't that a heavy task, especially if the word is an hot word?

            What is done in practice in such search systems?

            Maybe some tradeoff are being used?

            Thanks!

            ...

            ANSWER

            Answered 2022-Mar-24 at 17:25

            First of all, there are two types of indexes: local and global.

            A local index is stored on the same computer as tweet data. For example, you may have 10 shards and each of these shards will have its own index; like word "car" -> sorted list of tweet ids.

            When search is run we will have to send the query to every server. As we don't know where the most popular tweets are. That query will ask every server to return their top results. All of these results will be collected on the same box - the one executing the user request - and that process will pick top 10 of of entire population.

            Since all results are already sorted in the index itself, it is a O(1) operation to pick top 10 results from all lists - as we will be doing simple heap/watermarking on set number of tweets.

            Second nice property, we can do pagination - the next query will be also sent to every box with additional data - give me top 10, with popularity below X, where X is the popularity of last tweet returned to customer.

            Global index is a different beast - it does not live on the same boxes as data (it could, but does not have to). In that case, when we search for a keyword, we know exactly where to look for. And the index itself is also sorted, hence it is fast to get top 10 most popular results (or get pagination).

            Since the global index returns only tweet Ids and not tweet itself, we will have to lookup tweets for every id - this is called N+1 problem - 1 query to get a list of ids and then one query for every id. There are several ways to solve this - caching and data duplication are by far most common approaches.

            Source https://stackoverflow.com/questions/71588238

            QUESTION

            Unnest Query optimisation for singular record
            Asked 2022-Mar-24 at 11:45

            I'm trying to optimise my query for when an internal customer only want to return one result *(and it's associated nested dataset). My aim is to reduce the query process size.

            However, it appears to be the exact same value regardless of whether I'm querying for 1 record (with unnested 48,000 length array) or the whole dataset (10,000 records with unnest total 514,048,748 in total length of arrays)!

            So my table results for one record query:

            ...

            ANSWER

            Answered 2022-Mar-24 at 11:45

            This is happening because there is still need for a full table scan to find all the test IDs that are equal to the specified one.

            It is not clear from your example which columns are part of the timeseries record. In case test_id is not one of them, I would suggest to cluster the table on the test_id column. By clustering, the data will be automatically organized according to the contents of the test_id column.

            So, when you query with a filter on that column a full scan won't be needed to find all values.

            Read more about clustered tables here.

            Source https://stackoverflow.com/questions/71599650

            QUESTION

            handling million of rows for lookup operation using python
            Asked 2022-Mar-19 at 11:27

            I am new to data handling . I need to create python program to search a record from a samplefile1 in samplefile2. i am able to achieve it but for each record out of 200 rows in samplefile1 is looped over 200 rows in samplefile2 , it took 180 seconds complete execution time.

            I am looking for something to be more time efficient so that i can do this task in minimum time .

            My actual Dataset size is : 9million -> samplefile1 and 9million --> samplefile2.

            Here is my code using Pandas.

            sample1file1 rows:

            ...

            ANSWER

            Answered 2022-Mar-19 at 11:27

            I don't think using Pandas is helping here as you are just comparing whole lines. An alternative approach would be to load the first file as a set of lines. Then enumerate over the lines in the second file testing if it is in the set. This will be much faster:

            Source https://stackoverflow.com/questions/71526523

            QUESTION

            split function does not return any observations with large dataset
            Asked 2022-Mar-12 at 22:29

            I have a dataframe like this:

            ...

            ANSWER

            Answered 2022-Mar-12 at 22:29

            It is just that there are many unused levels as the column 'seqnames' is a factor. With split, there is an option to drop (drop = TRUE - by default it is FALSE) to remove those list elements. Otherwise, they will return as data.frame with 0 rows. If we want those elements to be replaced by NULL, then find those elements where the number of rows (nrow) are 0 and assign it to NULL

            Source https://stackoverflow.com/questions/71453084

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

            Vulnerabilities

            No vulnerabilities reported

            Install Cassandra-Java-Driver-Research

            You can download it from GitHub.
            You can use Cassandra-Java-Driver-Research like any standard Java library. Please include the the jar files in your classpath. You can also use any IDE and you can run and debug the Cassandra-Java-Driver-Research component as you would do with any other Java program. Best practice is to use a build tool that supports dependency management such as Maven or Gradle. For Maven installation, please refer maven.apache.org. For Gradle installation, please refer gradle.org .

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